The curve of relationship between fatigue crack growth rate and the stress strength factor amplitude represented an important fatigue property in designing of damage tolerance limits and predicting life of metallic co...The curve of relationship between fatigue crack growth rate and the stress strength factor amplitude represented an important fatigue property in designing of damage tolerance limits and predicting life of metallic component parts. In order to have a more reasonable use of testing data, samples from population were stratified suggested by the stratified random sample model (SRAM). The data in each stratum corresponded to the same experiment conditions. A suitable weight was assigned to each stratified sample according to the actual working states of the pressure vessel, so that the estimation of fatigue crack growth rate equation was more accurate for practice. An empirical study shows that the SRAM estimation by using fatigue crack growth rate data from different stoves is obviously better than the estimation from simple random sample model.展开更多
Variance is one of the most vital measures of dispersion widely employed in practical aspects.A commonly used approach for variance estimation is the traditional method of moments that is strongly influenced by the pr...Variance is one of the most vital measures of dispersion widely employed in practical aspects.A commonly used approach for variance estimation is the traditional method of moments that is strongly influenced by the presence of extreme values,and thus its results cannot be relied on.Finding momentum from Koyuncu’s recent work,the present paper focuses first on proposing two classes of variance estimators based on linear moments(L-moments),and then employing them with auxiliary data under double stratified sampling to introduce a new class of calibration variance estimators using important properties of L-moments(L-location,L-cv,L-variance).Three populations are taken into account to assess the efficiency of the new estimators.The first and second populations are concerned with artificial data,and the third populations is concerned with real data.The percentage relative efficiency of the proposed estimators over existing ones is evaluated.In the presence of extreme values,our findings depict the superiority and high efficiency of the proposed classes over traditional classes.Hence,when auxiliary data is available along with extreme values,the proposed classes of estimators may be implemented in an extensive variety of sampling surveys.展开更多
In general the accuracy of mean estimator can be improved by stratified random sampling. In this paper, we provide an idea different from empirical methods that the accuracy can be more improved through bootstrap resa...In general the accuracy of mean estimator can be improved by stratified random sampling. In this paper, we provide an idea different from empirical methods that the accuracy can be more improved through bootstrap resampling method under some conditions. The determination of sample size by bootstrap method is also discussed, and a simulation is made to verify the accuracy of the proposed method. The simulation results show that the sample size based on bootstrapping is smaller than that based on central limit theorem.展开更多
In this paper, analysis of methodology was realized for the application of stratified random sampling with optimum allocation in the case of a subject of research which concerns the rural population and presents high ...In this paper, analysis of methodology was realized for the application of stratified random sampling with optimum allocation in the case of a subject of research which concerns the rural population and presents high differentiations among the three strata in which this population could be classified. The rural population of Evros Prefecture （Greece） with criterion the mean altitude of settlements was classified in three strata, the mountainous, semi-mountainous and fiat population for the estimation of mean consumption of forest fuelwood for covering of heating and cooking needs in households of these three strata. The analysis of this methodology includes： （1） the determination of total size of sample for entire the rural population and its allocation to the various strata; （2） the investigation of effectiveness of stratification with the technique of analysis of variance （One-Way ANOVA）; （3） the conduct of sampling research with the realization of face-to-face interviews in selected households and （4） the control of forms of the questionnaire and the analysis of data by using the statistical package for social sciences, SPSS for Windows. All data for the analysis of this methodology and its practical application were taken by the pilot sampling which was realized in each stratum. Relative paper was not found by the review of literature.展开更多
In this paper, auxiliary information is used to determine an estimator of finite population total using nonparametric regression under stratified random sampling. To achieve this, a model-based approach is adopted by ...In this paper, auxiliary information is used to determine an estimator of finite population total using nonparametric regression under stratified random sampling. To achieve this, a model-based approach is adopted by making use of the local polynomial regression estimation to predict the nonsampled values of the survey variable y. The performance of the proposed estimator is investigated against some design-based and model-based regression estimators. The simulation experiments show that the resulting estimator exhibits good properties. Generally, good confidence intervals are seen for the nonparametric regression estimators, and use of the proposed estimator leads to relatively smaller values of RE compared to other estimators.展开更多
Fishery-independent surveys are often used for collecting high quality biological and ecological data to support fisheries management. A careful optimization of fishery-independent survey design is necessary to improv...Fishery-independent surveys are often used for collecting high quality biological and ecological data to support fisheries management. A careful optimization of fishery-independent survey design is necessary to improve the precision of survey estimates with cost-effective sampling efforts. We developed a simulation approach to evaluate and optimize the stratification scheme for a fishery-independent survey with multiple goals including estimation of abundance indices of individual species and species diversity indices. We compared the performances of the sampling designs with different stratification schemes for different goals over different months. Gains in precision of survey estimates from the stratification schemes were acquired compared to simple random sampling design for most indices. The stratification scheme with five strata performed the best. This study showed that the loss of precision of survey estimates due to the reduction of sampling efforts could be compensated by improved stratification schemes, which would reduce the cost and negative impacts of survey trawling on those species with low abundance in the fishery-independent survey. This study also suggests that optimization of a survey design differed with different survey objectives. A post-survey analysis can improve the stratification scheme of fishery-independent survey designs.展开更多
Natural resource statistics are often unavailable for small ecological or economic regions and policymakers have to rely on state-level datasets to evaluate the status of their resources （i.e., forests, rangelands, g...Natural resource statistics are often unavailable for small ecological or economic regions and policymakers have to rely on state-level datasets to evaluate the status of their resources （i.e., forests, rangelands, grasslands, agriculture, etc.） at the regional or local level. These resources can be evaluated using small-area estimation techniques. However, it is unknown which small area technique produces the most valid and precise results. The reliability and accuracy of two methods, synthetic and regression estimators, used in smallarea analyses, were examined in this study. The two small-area analysis methods were applied to data from Jalisco＇s state-wide natural resource inventory to examine how well each technique predicted selected characteristics of forest stand structure. The regression method produced the most valid and precise estimates of forest stand characteristics at multiple geographical scales. Therefore, state and local resource managers should utilize the regression method unless appropriate auxiliary information is not available.展开更多
Digital soil mapping (DSM) aims to produce detailed maps of soil properties or soil classes to improve agricultural management and soil quality assessment. Optimized sampling design can reduce the substantial costs an...Digital soil mapping (DSM) aims to produce detailed maps of soil properties or soil classes to improve agricultural management and soil quality assessment. Optimized sampling design can reduce the substantial costs and efforts associated with sampling, profile description, and laboratory analysis. The purpose of this study was to compare common sampling designs for DSM, including grid sampling (GS), grid random sampling (GRS), stratified random sampling (StRS), and conditioned Latin hypercube sampling (cLHS). In an agricultural field (11 ha) in Quebec, Canada, a total of unique 118 locations were selected using each of the four sampling designs (45 locations each), and additional 30 sample locations were selected as an independent testing dataset (evaluation dataset). Soil visible near-infrared (Vis-NIR) spectra were collected in situ at the 148 locations (1 m depth), and soil cores were collected from a subset of 32 locations and subdivided at 10-cm depth intervals, totaling 251 samples. The Cubist model was used to elucidate the relationship between Vis-NIR spectra and soil properties (soil organic matter (SOM) and clay), which was then used to predict the soil properties at all 148 sample locations. Digital maps of soil properties at multiple depths for the entire field (148 sample locations) were prepared using a quantile random forest model to obtain complete model maps (CM-maps). Soil properties were also mapped using the samples from each of the 45 locations for each sampling design to obtain sampling design maps (SD-maps). The SD-maps were evaluated using the independent testing dataset (30 sample locations), and the spatial distribution and model uncertainty of each SD-map were compared with those of the corresponding CM-map. The spatial and feature space coverage were compared across the four sampling designs. The results showed that GS resulted in the most even spatial coverage, cLHS resulted in the best coverage of the feature space, and GS and cLHS resulted in similar prediction accuracies and spatial distributions of soil properties. The SOM content was underestimated using GRS, with large errors at 0–50 cm depth, due to some values not being captured by this sampling design, whereas larger errors for the deeper soil layers were produced using StRS. Predictions of SOM and clay contents had higher accuracy for topsoil (0–30 cm) than for deep subsoil (60–100 cm). It was concluded that the soil sampling designs with either good spatial coverage or feature space coverage can provide good accuracy in 3D DSM, but their performances may be different for different soil properties.展开更多
Variance is one of themost important measures of descriptive statistics and commonly used for statistical analysis.The traditional second-order central moment based variance estimation is a widely utilized methodology...Variance is one of themost important measures of descriptive statistics and commonly used for statistical analysis.The traditional second-order central moment based variance estimation is a widely utilized methodology.However,traditional variance estimator is highly affected in the presence of extreme values.So this paper initially,proposes two classes of calibration estimators based on an adaptation of the estimators recently proposed by Koyuncu and then presents a new class of L-Moments based calibration variance estimators utilizing L-Moments characteristics(L-location,Lscale,L-CV)and auxiliary information.It is demonstrated that the proposed L-Moments based calibration variance estimators are more efficient than adapted ones.Artificial data is considered for assessing the performance of the proposed estimators.We also demonstrated an application related to apple fruit for purposes of the article.Using artificial and real data sets,percentage relative efficiency(PRE)of the proposed class of estimators with respect to adapted ones are calculated.The PRE results indicate to the superiority of the proposed class over adapted ones in the presence of extreme values.In this manner,the proposed class of estimators could be applied over an expansive range of survey sampling whenever auxiliary information is available in the presence of extreme values.展开更多
This paper reveaed some problems of the forest samling investigation from application.and pointed out the defects. Determining sample size method was precisely put forward from formla's origin in simple random Sam...This paper reveaed some problems of the forest samling investigation from application.and pointed out the defects. Determining sample size method was precisely put forward from formla's origin in simple random Samling procedure In stratified random samgling, two cases were distinguished: the variances Sh2 are equal for all h and not all Sh2 are equal This method made the assertion of making confidence interval more reliable.展开更多
Climate change has become a global phenomenon and is adversely affecting agricultural development across the globe.Developing countries like Pakistan where 18.9%of the GDP(gross domestic product)came from the agricult...Climate change has become a global phenomenon and is adversely affecting agricultural development across the globe.Developing countries like Pakistan where 18.9%of the GDP(gross domestic product)came from the agriculture sector and also 42%of the labor force involved in agriculture.They are directly and indirectly affected by climate change due to an increase in the frequency and intensity of climatic extreme events such as floods,droughts and extreme weather events.In this paper,we have focused on the impact of climate change on farm households and their adaptation strategies to cope up the climatic extremes.For this purpose,we have selected farm households by using multistage stratified random sampling from four districts of the Potohar region i.e.Attock,Rawalpindi,Jhelum and Chakwal.These districts were selected by dividing the Potohar region into rain-fed areas.We have employed logistic regression to assess the determinants of adaptation to climate change and its impact.We have also calculated the marginal effect of each independent variable of the logistic regression to measure the immediate rate of change in the model.In order to check the significance of our suggested model,we have used hypothesis testing.展开更多
Coverage of nominal 95% confidence intervals of a proportion estimated from a sample obtained under a complex survey design, or a proportion estimated from a ratio of two random variables, can depart significantly fro...Coverage of nominal 95% confidence intervals of a proportion estimated from a sample obtained under a complex survey design, or a proportion estimated from a ratio of two random variables, can depart significantly from its target. Effective calibration methods exist for intervals for a proportion derived from a single binary study variable, but not for estimates of thematic classification accuracy. To promote a calibration of confidence intervals within the context of land-cover mapping, this study first illustrates a common problem of under and over-coverage with standard confidence intervals, and then proposes a simple and fast calibration that more often than not will improve coverage. The demonstration is with simulated sampling from a classified map with four classes, and a reference class known for every unit in a population of 160,000 units arranged in a square array. The simulations include four common probability sampling designs for accuracy assessment, and three sample sizes. Statistically significant over- and under-coverage was present in estimates of user’s (UA) and producer’s accuracy (PA) as well as in estimates of class area proportion. A calibration with Bayes intervals for UA and PA was most efficient with smaller sample sizes and two cluster sampling designs.展开更多
Stratified random survey is commonly used to estimate abundance indices of fish populations in multispecies survey,providing reliable data for stock assessment and fisheries management.In some cases,however,the sample...Stratified random survey is commonly used to estimate abundance indices of fish populations in multispecies survey,providing reliable data for stock assessment and fisheries management.In some cases,however,the sample size is relatively small because of the limitation of survey cost or other factors.The allocation methods of sampling efforts among strata in stratified random surveys with small sample size may need adjustment compared with traditional approaches.In this study,two sampling stations were allocated to each stratum first and then the remaining sampling units were allocated among strata using five traditional allocation methods.In order to distinguish them from traditional methods,we called them adjusted methods in this study.A simulation study was conducted to compare the performances of different allocation strategies of sampling efforts in a stratified random survey for estimating abundance indices of multiple target species.Relative estimation error(REE)and relative bias(RB)were used to measure the precision and accuracy of estimates of abundance indices under different allocation schemes of sampling efforts in the multispecies survey.The performances of different allocation schemes in estimating abundance indices varied greatly for different species over different seasons.The adjusted Neyman allocation scheme could significantly reduce the REE and RB of estimates of abundance index for single species survey.For multiple species surveys,the adjusted average-Neyman allocation method,the adjusted Yate allocation method,the adjusted proportional allocation method and current allocation method had relatively high accuracy and precision of estimates of abundance indices for four species in terms of the total_(REE) and total_(RB).Though the adjusted average-Neyman allocation scheme did not always have the best performance,it was the optimal one considering the accuracy and precision of estimates of abundance indices for all species simultaneously.The allocation of sampling efforts among strata in stratified random surveys targeting for estimating abundance indices of multiple species should comprehensively consider the variance of abundance of different species in stratum and the seasonal changes.展开更多
Suppose that several different imperfect instruments and one perfect instrument are used independently to measure some characteristic of a population. In order to make full use of the sample information, in this paper...Suppose that several different imperfect instruments and one perfect instrument are used independently to measure some characteristic of a population. In order to make full use of the sample information, in this paper the empirical likelihood method is put forward for making inferences on parameters of interest under stratified random sampling in the presence of measurement error, Our results show that it can lead to estimators which are asymptotically normal and utilize all the available sample information. We also obtain the asymptotic distribution of empirical likelihood testing statistics. In particular, we apply the method to obtain estimator and confidence interval of population mean.展开更多
In the realm of survey data analysis,encountering substantial variance relative to bias is a common occurrence.In this study,we present an innovative strategy to tackle this issue by introducing slightly biased varian...In the realm of survey data analysis,encountering substantial variance relative to bias is a common occurrence.In this study,we present an innovative strategy to tackle this issue by introducing slightly biased variance estimators.These estimators incorporate a constant c within the range of 0 to 1,which is determined through the minimization of Mean Squared Error(MSE)for c×(variance estimator).This research builds upon the foundation laid by Kourouklis(2012,A new estimator of the variance based on minimizing mean squared error.The American Statistician,66(4),234–236)and extends their work into the domain of survey sampling.Extensive simulation studies are conducted to illustrate the superior performance of the adjusted variance estimators when compared to standard variance estimators,particularly in terms of MSE.These findings underscore the efficacy of our proposed approach in enhancing the precision of variance estimation within the context of survey data analysis.展开更多
Objective To study the mechanism of Qingfu Daotan(QFDT)Formula in improving polycystic ovary syndromeinsulin resistance(PCOS-IR)based on intestinal flora.Methods Totally 65 female SD rats with normal estrous cycle wer...Objective To study the mechanism of Qingfu Daotan(QFDT)Formula in improving polycystic ovary syndromeinsulin resistance(PCOS-IR)based on intestinal flora.Methods Totally 65 female SD rats with normal estrous cycle were divided into 6 groups according to the weight stratified randomization method:control group,PCOS-IR group,metformin group,QFDT-low dose group(QFDT-L),QFDT-normal dose group(QFDT-N),and QFDT-high dose group(QFDT-H).展开更多
Introduction:Nutrition knowledge(NK)is a key modifiable factor influencing the dietary behavior and nutritional status of children.Currently,nationally representative data assessing NK among Chinese junior high school...Introduction:Nutrition knowledge(NK)is a key modifiable factor influencing the dietary behavior and nutritional status of children.Currently,nationally representative data assessing NK among Chinese junior high school students are unavailable.This study aimed to assess NK levels using recent,nationally representative data from China.Methods:A multistage stratified random cluster sampling method was used to select 28,629 junior high school students from 195 survey sites across 31 provincial-level administrative divisions in China.Data were collected using a standardized questionnaire developed using rigorous scientific procedures.NK awareness rates were described as weighted prevalence rates with 95%confidence intervals(CIs).Subgroup comparisons were performed using the Rao–Scott chisquare test.Results:The overall NK awareness rate among Chinese junior high school students was 40.0%(95%CI:36.5%–43.5%).The rates for the five dimensions,dietary recommendations,nutrient content of foods,food and health,food choices,and food safety,were 20.1%,46.2%,65.3%,65.2%,and 65.2%,respectively.The analysis revealed significant variations in overall and dimension-specific awareness rates across groups.Boys,students from rural and western regions,and students from families with lower socioeconomic status had poorer NK levels than their counterparts.Among the 10 knowledge points with the lowest correct rates,seven belonged to dietary recommendations,two to food safety,and one to food and health.Conclusion:NK awareness rates among junior high school students require improvement,especially regarding dietary recommendations,which remain a key component of students’nutrition education.Boys,students from rural and western regions,and students from families with lower socioeconomic status should be the key populations for NK dissemination in the future.展开更多
It has been a challenge to employ machine learning(ML)to optimize casting processes due to the scarcity of data and difficulty in feature expansion.Here,we introduce a nearest neighbor search method to optimize the st...It has been a challenge to employ machine learning(ML)to optimize casting processes due to the scarcity of data and difficulty in feature expansion.Here,we introduce a nearest neighbor search method to optimize the stratified random sampling in Latin hypercube sampling(LHS)and propose a new revised LHS coupled with Bayesian optimization(RLHS-BO).Using this method,we optimized the squeeze-casting process for mine fuel tank partition castings for the first time with an ultra-small dataset of 25 samples.Compared to traditional methods such as random sampling,interval sampling,orthogonal design(OD),and central composite design(CCD),our approach covers the process parameter space more,reduces the data volume by approximately 50%,and achieves process optimization beyond five factors-five levels with fewer data.Through RLHS and 6 iterations of experiments,the optimal process was identified,and the ultimate tensile strength(UTS)of partition casting under the optimal process reached 239.7 MPa,with an elongation(EL)of 12.2%,showing increases of 17.6%and 18.4%over the optimal values in the initial dataset.Finally,a combination of Shapley additive interpretation(SHAP)and phase-field method(PFM)of solidification dendrite growth was used to address the issue of weak physical interpretability in ML models.展开更多
Introduction:To evaluate the effectiveness of tobacco control efforts,we conducted a comprehensive analysis of trends in smoking cessation willingness and behavior among Chinese smokers from 2010 to 2024.Methods:Data ...Introduction:To evaluate the effectiveness of tobacco control efforts,we conducted a comprehensive analysis of trends in smoking cessation willingness and behavior among Chinese smokers from 2010 to 2024.Methods:Data were obtained from the 2010 Global Adult Tobacco Survey(GATS)-China Project and the National Adult Tobacco Survey(NATS)conducted in 2018,2022,and 2024.All surveys employed multistage stratified cluster random sampling of the Chinese population aged 15 years and above.Complex sampling analysis was performed for calculations,and trend analysis was conducted using the Cochran-Armitage trend test.Results:From 2010 to 2024,cessation behavior among Chinese smokers increased significantly.Cessation rates rose from 16.88%to 22.65%,and the proportion of smokers who attempted to quit in the past 12 months increased from 14.37%to 24.75%.The proportion of smokers planning to quit within 12 months increased from 16.10%to 21.61%from 2010 to 2022,but dropped to 16.07%in 2024.Over the 14-year period,cessation rates and quit attempts increased significantly across almost all demographic groups.However,from 2022 to 2024,cessation rates among daily smokers declined while the proportion of those willing to quit decreased.Occasional smokers consistently demonstrated higher cessation rates,quit attempts,and willingness to quit compared to daily smokers.Conclusions:The observed increases in cessation behavior may be attributed to expanded smoking cessation services and extensive cessation campaigns implemented over the years.Enhanced cessation interventions should be targeted toward daily smokers.Pricing policies,graphic health warnings on packaging,and community-based comprehensive smoking cessation interventions can further enhance smokers’willingness to quit and encourage more cessation attempts.展开更多
Urban planners must ensure that urban public spaces are enjoyable to use to create a lively city that expresses their culture and traditions and welcomes social diversity.This study aims to develop a theoretical index...Urban planners must ensure that urban public spaces are enjoyable to use to create a lively city that expresses their culture and traditions and welcomes social diversity.This study aims to develop a theoretical index for assessing the livability levels in tourist districts.Therefore,a survey-based study accompanied by a literature review is used to derive criteria for livability.In addition to using the analytic hierarchy process to develop an importa ncebased hierarchy of criteria,mathematical analysis is applied to derive the livability index.Furthermore,one of Sharjah's well-known public spaces,Al Qasba Tourist District,is assessed as a case study.This study discussed the main concepts and factors of livability in urban public spaces to examine the livable extent of Qasba and the significanee of criteria.Results show that the current livability level in Al Qasba is less than 50%,confirming its urgent need for further urban improvement.This study explores the livability assessment criteria and their influencing parameters.Using the suggested conceptual livability in dexen ables decision makers to assess the livability level,analyze the in fluencing factors,and suggest solutions to improve the overall livability levels of open public spaces.展开更多
文摘The curve of relationship between fatigue crack growth rate and the stress strength factor amplitude represented an important fatigue property in designing of damage tolerance limits and predicting life of metallic component parts. In order to have a more reasonable use of testing data, samples from population were stratified suggested by the stratified random sample model (SRAM). The data in each stratum corresponded to the same experiment conditions. A suitable weight was assigned to each stratified sample according to the actual working states of the pressure vessel, so that the estimation of fatigue crack growth rate equation was more accurate for practice. An empirical study shows that the SRAM estimation by using fatigue crack growth rate data from different stoves is obviously better than the estimation from simple random sample model.
基金The authors thank the Deanship of Scientific Research at King Khalid University,Kingdom of Saudi Arabia for funding this study through the research groups program under Project Number R.G.P.1/64/42.Ishfaq Ahmad and Ibrahim Mufrah Almanjahie received the grant.
文摘Variance is one of the most vital measures of dispersion widely employed in practical aspects.A commonly used approach for variance estimation is the traditional method of moments that is strongly influenced by the presence of extreme values,and thus its results cannot be relied on.Finding momentum from Koyuncu’s recent work,the present paper focuses first on proposing two classes of variance estimators based on linear moments(L-moments),and then employing them with auxiliary data under double stratified sampling to introduce a new class of calibration variance estimators using important properties of L-moments(L-location,L-cv,L-variance).Three populations are taken into account to assess the efficiency of the new estimators.The first and second populations are concerned with artificial data,and the third populations is concerned with real data.The percentage relative efficiency of the proposed estimators over existing ones is evaluated.In the presence of extreme values,our findings depict the superiority and high efficiency of the proposed classes over traditional classes.Hence,when auxiliary data is available along with extreme values,the proposed classes of estimators may be implemented in an extensive variety of sampling surveys.
基金The Science Research Start-up Foundation for Young Teachers of Southwest Jiaotong University(No.2007Q091)
文摘In general the accuracy of mean estimator can be improved by stratified random sampling. In this paper, we provide an idea different from empirical methods that the accuracy can be more improved through bootstrap resampling method under some conditions. The determination of sample size by bootstrap method is also discussed, and a simulation is made to verify the accuracy of the proposed method. The simulation results show that the sample size based on bootstrapping is smaller than that based on central limit theorem.
文摘In this paper, analysis of methodology was realized for the application of stratified random sampling with optimum allocation in the case of a subject of research which concerns the rural population and presents high differentiations among the three strata in which this population could be classified. The rural population of Evros Prefecture （Greece） with criterion the mean altitude of settlements was classified in three strata, the mountainous, semi-mountainous and fiat population for the estimation of mean consumption of forest fuelwood for covering of heating and cooking needs in households of these three strata. The analysis of this methodology includes： （1） the determination of total size of sample for entire the rural population and its allocation to the various strata; （2） the investigation of effectiveness of stratification with the technique of analysis of variance （One-Way ANOVA）; （3） the conduct of sampling research with the realization of face-to-face interviews in selected households and （4） the control of forms of the questionnaire and the analysis of data by using the statistical package for social sciences, SPSS for Windows. All data for the analysis of this methodology and its practical application were taken by the pilot sampling which was realized in each stratum. Relative paper was not found by the review of literature.
文摘In this paper, auxiliary information is used to determine an estimator of finite population total using nonparametric regression under stratified random sampling. To achieve this, a model-based approach is adopted by making use of the local polynomial regression estimation to predict the nonsampled values of the survey variable y. The performance of the proposed estimator is investigated against some design-based and model-based regression estimators. The simulation experiments show that the resulting estimator exhibits good properties. Generally, good confidence intervals are seen for the nonparametric regression estimators, and use of the proposed estimator leads to relatively smaller values of RE compared to other estimators.
基金The Public Science and Technology Research Funds Projects of Ocean under contract No.201305030the Specialized Research Fund for the Doctoral Program of Higher Education under contract No.20120132130001
文摘Fishery-independent surveys are often used for collecting high quality biological and ecological data to support fisheries management. A careful optimization of fishery-independent survey design is necessary to improve the precision of survey estimates with cost-effective sampling efforts. We developed a simulation approach to evaluate and optimize the stratification scheme for a fishery-independent survey with multiple goals including estimation of abundance indices of individual species and species diversity indices. We compared the performances of the sampling designs with different stratification schemes for different goals over different months. Gains in precision of survey estimates from the stratification schemes were acquired compared to simple random sampling design for most indices. The stratification scheme with five strata performed the best. This study showed that the loss of precision of survey estimates due to the reduction of sampling efforts could be compensated by improved stratification schemes, which would reduce the cost and negative impacts of survey trawling on those species with low abundance in the fishery-independent survey. This study also suggests that optimization of a survey design differed with different survey objectives. A post-survey analysis can improve the stratification scheme of fishery-independent survey designs.
文摘Natural resource statistics are often unavailable for small ecological or economic regions and policymakers have to rely on state-level datasets to evaluate the status of their resources （i.e., forests, rangelands, grasslands, agriculture, etc.） at the regional or local level. These resources can be evaluated using small-area estimation techniques. However, it is unknown which small area technique produces the most valid and precise results. The reliability and accuracy of two methods, synthetic and regression estimators, used in smallarea analyses, were examined in this study. The two small-area analysis methods were applied to data from Jalisco＇s state-wide natural resource inventory to examine how well each technique predicted selected characteristics of forest stand structure. The regression method produced the most valid and precise estimates of forest stand characteristics at multiple geographical scales. Therefore, state and local resource managers should utilize the regression method unless appropriate auxiliary information is not available.
基金the National Science and Engineering Research Council of Canada(No.RGPIN-2014-04100)for funding this project.
文摘Digital soil mapping (DSM) aims to produce detailed maps of soil properties or soil classes to improve agricultural management and soil quality assessment. Optimized sampling design can reduce the substantial costs and efforts associated with sampling, profile description, and laboratory analysis. The purpose of this study was to compare common sampling designs for DSM, including grid sampling (GS), grid random sampling (GRS), stratified random sampling (StRS), and conditioned Latin hypercube sampling (cLHS). In an agricultural field (11 ha) in Quebec, Canada, a total of unique 118 locations were selected using each of the four sampling designs (45 locations each), and additional 30 sample locations were selected as an independent testing dataset (evaluation dataset). Soil visible near-infrared (Vis-NIR) spectra were collected in situ at the 148 locations (1 m depth), and soil cores were collected from a subset of 32 locations and subdivided at 10-cm depth intervals, totaling 251 samples. The Cubist model was used to elucidate the relationship between Vis-NIR spectra and soil properties (soil organic matter (SOM) and clay), which was then used to predict the soil properties at all 148 sample locations. Digital maps of soil properties at multiple depths for the entire field (148 sample locations) were prepared using a quantile random forest model to obtain complete model maps (CM-maps). Soil properties were also mapped using the samples from each of the 45 locations for each sampling design to obtain sampling design maps (SD-maps). The SD-maps were evaluated using the independent testing dataset (30 sample locations), and the spatial distribution and model uncertainty of each SD-map were compared with those of the corresponding CM-map. The spatial and feature space coverage were compared across the four sampling designs. The results showed that GS resulted in the most even spatial coverage, cLHS resulted in the best coverage of the feature space, and GS and cLHS resulted in similar prediction accuracies and spatial distributions of soil properties. The SOM content was underestimated using GRS, with large errors at 0–50 cm depth, due to some values not being captured by this sampling design, whereas larger errors for the deeper soil layers were produced using StRS. Predictions of SOM and clay contents had higher accuracy for topsoil (0–30 cm) than for deep subsoil (60–100 cm). It was concluded that the soil sampling designs with either good spatial coverage or feature space coverage can provide good accuracy in 3D DSM, but their performances may be different for different soil properties.
基金The authors are grateful to the Deanship of Scientific Research at King Khalid University,Kingdom of Saudi Arabia for funding this study through the research groups program under project number R.G.P.2/67/41.Ibrahim Mufrah Almanjahie received the grant.
文摘Variance is one of themost important measures of descriptive statistics and commonly used for statistical analysis.The traditional second-order central moment based variance estimation is a widely utilized methodology.However,traditional variance estimator is highly affected in the presence of extreme values.So this paper initially,proposes two classes of calibration estimators based on an adaptation of the estimators recently proposed by Koyuncu and then presents a new class of L-Moments based calibration variance estimators utilizing L-Moments characteristics(L-location,Lscale,L-CV)and auxiliary information.It is demonstrated that the proposed L-Moments based calibration variance estimators are more efficient than adapted ones.Artificial data is considered for assessing the performance of the proposed estimators.We also demonstrated an application related to apple fruit for purposes of the article.Using artificial and real data sets,percentage relative efficiency(PRE)of the proposed class of estimators with respect to adapted ones are calculated.The PRE results indicate to the superiority of the proposed class over adapted ones in the presence of extreme values.In this manner,the proposed class of estimators could be applied over an expansive range of survey sampling whenever auxiliary information is available in the presence of extreme values.
文摘This paper reveaed some problems of the forest samling investigation from application.and pointed out the defects. Determining sample size method was precisely put forward from formla's origin in simple random Samling procedure In stratified random samgling, two cases were distinguished: the variances Sh2 are equal for all h and not all Sh2 are equal This method made the assertion of making confidence interval more reliable.
文摘Climate change has become a global phenomenon and is adversely affecting agricultural development across the globe.Developing countries like Pakistan where 18.9%of the GDP(gross domestic product)came from the agriculture sector and also 42%of the labor force involved in agriculture.They are directly and indirectly affected by climate change due to an increase in the frequency and intensity of climatic extreme events such as floods,droughts and extreme weather events.In this paper,we have focused on the impact of climate change on farm households and their adaptation strategies to cope up the climatic extremes.For this purpose,we have selected farm households by using multistage stratified random sampling from four districts of the Potohar region i.e.Attock,Rawalpindi,Jhelum and Chakwal.These districts were selected by dividing the Potohar region into rain-fed areas.We have employed logistic regression to assess the determinants of adaptation to climate change and its impact.We have also calculated the marginal effect of each independent variable of the logistic regression to measure the immediate rate of change in the model.In order to check the significance of our suggested model,we have used hypothesis testing.
文摘Coverage of nominal 95% confidence intervals of a proportion estimated from a sample obtained under a complex survey design, or a proportion estimated from a ratio of two random variables, can depart significantly from its target. Effective calibration methods exist for intervals for a proportion derived from a single binary study variable, but not for estimates of thematic classification accuracy. To promote a calibration of confidence intervals within the context of land-cover mapping, this study first illustrates a common problem of under and over-coverage with standard confidence intervals, and then proposes a simple and fast calibration that more often than not will improve coverage. The demonstration is with simulated sampling from a classified map with four classes, and a reference class known for every unit in a population of 160,000 units arranged in a square array. The simulations include four common probability sampling designs for accuracy assessment, and three sample sizes. Statistically significant over- and under-coverage was present in estimates of user’s (UA) and producer’s accuracy (PA) as well as in estimates of class area proportion. A calibration with Bayes intervals for UA and PA was most efficient with smaller sample sizes and two cluster sampling designs.
基金This work was funded by the National Key R&D Program of China(2018YFD0900904)the National Natural Science Foundation of China(31772852)the Fundamental Research Funds for the Central Universities(No.201562030,No.201612004).
文摘Stratified random survey is commonly used to estimate abundance indices of fish populations in multispecies survey,providing reliable data for stock assessment and fisheries management.In some cases,however,the sample size is relatively small because of the limitation of survey cost or other factors.The allocation methods of sampling efforts among strata in stratified random surveys with small sample size may need adjustment compared with traditional approaches.In this study,two sampling stations were allocated to each stratum first and then the remaining sampling units were allocated among strata using five traditional allocation methods.In order to distinguish them from traditional methods,we called them adjusted methods in this study.A simulation study was conducted to compare the performances of different allocation strategies of sampling efforts in a stratified random survey for estimating abundance indices of multiple target species.Relative estimation error(REE)and relative bias(RB)were used to measure the precision and accuracy of estimates of abundance indices under different allocation schemes of sampling efforts in the multispecies survey.The performances of different allocation schemes in estimating abundance indices varied greatly for different species over different seasons.The adjusted Neyman allocation scheme could significantly reduce the REE and RB of estimates of abundance index for single species survey.For multiple species surveys,the adjusted average-Neyman allocation method,the adjusted Yate allocation method,the adjusted proportional allocation method and current allocation method had relatively high accuracy and precision of estimates of abundance indices for four species in terms of the total_(REE) and total_(RB).Though the adjusted average-Neyman allocation scheme did not always have the best performance,it was the optimal one considering the accuracy and precision of estimates of abundance indices for all species simultaneously.The allocation of sampling efforts among strata in stratified random surveys targeting for estimating abundance indices of multiple species should comprehensively consider the variance of abundance of different species in stratum and the seasonal changes.
基金Supported by the National Natural Science Foundation of China （No.10171051）
文摘Suppose that several different imperfect instruments and one perfect instrument are used independently to measure some characteristic of a population. In order to make full use of the sample information, in this paper the empirical likelihood method is put forward for making inferences on parameters of interest under stratified random sampling in the presence of measurement error, Our results show that it can lead to estimators which are asymptotically normal and utilize all the available sample information. We also obtain the asymptotic distribution of empirical likelihood testing statistics. In particular, we apply the method to obtain estimator and confidence interval of population mean.
文摘In the realm of survey data analysis,encountering substantial variance relative to bias is a common occurrence.In this study,we present an innovative strategy to tackle this issue by introducing slightly biased variance estimators.These estimators incorporate a constant c within the range of 0 to 1,which is determined through the minimization of Mean Squared Error(MSE)for c×(variance estimator).This research builds upon the foundation laid by Kourouklis(2012,A new estimator of the variance based on minimizing mean squared error.The American Statistician,66(4),234–236)and extends their work into the domain of survey sampling.Extensive simulation studies are conducted to illustrate the superior performance of the adjusted variance estimators when compared to standard variance estimators,particularly in terms of MSE.These findings underscore the efficacy of our proposed approach in enhancing the precision of variance estimation within the context of survey data analysis.
文摘Objective To study the mechanism of Qingfu Daotan(QFDT)Formula in improving polycystic ovary syndromeinsulin resistance(PCOS-IR)based on intestinal flora.Methods Totally 65 female SD rats with normal estrous cycle were divided into 6 groups according to the weight stratified randomization method:control group,PCOS-IR group,metformin group,QFDT-low dose group(QFDT-L),QFDT-normal dose group(QFDT-N),and QFDT-high dose group(QFDT-H).
基金Approved by the Medical Ethical Review Committee of the National Institute for Nutrition and Health,Chinese Center for Disease Control and Prevention(No.2022-037).
文摘Introduction:Nutrition knowledge(NK)is a key modifiable factor influencing the dietary behavior and nutritional status of children.Currently,nationally representative data assessing NK among Chinese junior high school students are unavailable.This study aimed to assess NK levels using recent,nationally representative data from China.Methods:A multistage stratified random cluster sampling method was used to select 28,629 junior high school students from 195 survey sites across 31 provincial-level administrative divisions in China.Data were collected using a standardized questionnaire developed using rigorous scientific procedures.NK awareness rates were described as weighted prevalence rates with 95%confidence intervals(CIs).Subgroup comparisons were performed using the Rao–Scott chisquare test.Results:The overall NK awareness rate among Chinese junior high school students was 40.0%(95%CI:36.5%–43.5%).The rates for the five dimensions,dietary recommendations,nutrient content of foods,food and health,food choices,and food safety,were 20.1%,46.2%,65.3%,65.2%,and 65.2%,respectively.The analysis revealed significant variations in overall and dimension-specific awareness rates across groups.Boys,students from rural and western regions,and students from families with lower socioeconomic status had poorer NK levels than their counterparts.Among the 10 knowledge points with the lowest correct rates,seven belonged to dietary recommendations,two to food safety,and one to food and health.Conclusion:NK awareness rates among junior high school students require improvement,especially regarding dietary recommendations,which remain a key component of students’nutrition education.Boys,students from rural and western regions,and students from families with lower socioeconomic status should be the key populations for NK dissemination in the future.
基金supported by the National Natural Science Foundation of China(Nos.52074246,52275390,52375394)National Defense Basic Scientific Research Program of China(Nos.JCKY2020408B002)Key R&D Program of Shanxi Province(Nos.202102050201011).
文摘It has been a challenge to employ machine learning(ML)to optimize casting processes due to the scarcity of data and difficulty in feature expansion.Here,we introduce a nearest neighbor search method to optimize the stratified random sampling in Latin hypercube sampling(LHS)and propose a new revised LHS coupled with Bayesian optimization(RLHS-BO).Using this method,we optimized the squeeze-casting process for mine fuel tank partition castings for the first time with an ultra-small dataset of 25 samples.Compared to traditional methods such as random sampling,interval sampling,orthogonal design(OD),and central composite design(CCD),our approach covers the process parameter space more,reduces the data volume by approximately 50%,and achieves process optimization beyond five factors-five levels with fewer data.Through RLHS and 6 iterations of experiments,the optimal process was identified,and the ultimate tensile strength(UTS)of partition casting under the optimal process reached 239.7 MPa,with an elongation(EL)of 12.2%,showing increases of 17.6%and 18.4%over the optimal values in the initial dataset.Finally,a combination of Shapley additive interpretation(SHAP)and phase-field method(PFM)of solidification dendrite growth was used to address the issue of weak physical interpretability in ML models.
基金Supported by National Major Scientific and Technological Special Project(2023ZD0506401)Global Health Capacity Building and Tobacco Control Project,Chinese Center for Disease Control and Prevention(2025).
文摘Introduction:To evaluate the effectiveness of tobacco control efforts,we conducted a comprehensive analysis of trends in smoking cessation willingness and behavior among Chinese smokers from 2010 to 2024.Methods:Data were obtained from the 2010 Global Adult Tobacco Survey(GATS)-China Project and the National Adult Tobacco Survey(NATS)conducted in 2018,2022,and 2024.All surveys employed multistage stratified cluster random sampling of the Chinese population aged 15 years and above.Complex sampling analysis was performed for calculations,and trend analysis was conducted using the Cochran-Armitage trend test.Results:From 2010 to 2024,cessation behavior among Chinese smokers increased significantly.Cessation rates rose from 16.88%to 22.65%,and the proportion of smokers who attempted to quit in the past 12 months increased from 14.37%to 24.75%.The proportion of smokers planning to quit within 12 months increased from 16.10%to 21.61%from 2010 to 2022,but dropped to 16.07%in 2024.Over the 14-year period,cessation rates and quit attempts increased significantly across almost all demographic groups.However,from 2022 to 2024,cessation rates among daily smokers declined while the proportion of those willing to quit decreased.Occasional smokers consistently demonstrated higher cessation rates,quit attempts,and willingness to quit compared to daily smokers.Conclusions:The observed increases in cessation behavior may be attributed to expanded smoking cessation services and extensive cessation campaigns implemented over the years.Enhanced cessation interventions should be targeted toward daily smokers.Pricing policies,graphic health warnings on packaging,and community-based comprehensive smoking cessation interventions can further enhance smokers’willingness to quit and encourage more cessation attempts.
文摘Urban planners must ensure that urban public spaces are enjoyable to use to create a lively city that expresses their culture and traditions and welcomes social diversity.This study aims to develop a theoretical index for assessing the livability levels in tourist districts.Therefore,a survey-based study accompanied by a literature review is used to derive criteria for livability.In addition to using the analytic hierarchy process to develop an importa ncebased hierarchy of criteria,mathematical analysis is applied to derive the livability index.Furthermore,one of Sharjah's well-known public spaces,Al Qasba Tourist District,is assessed as a case study.This study discussed the main concepts and factors of livability in urban public spaces to examine the livable extent of Qasba and the significanee of criteria.Results show that the current livability level in Al Qasba is less than 50%,confirming its urgent need for further urban improvement.This study explores the livability assessment criteria and their influencing parameters.Using the suggested conceptual livability in dexen ables decision makers to assess the livability level,analyze the in fluencing factors,and suggest solutions to improve the overall livability levels of open public spaces.
