We consider the estimation of nonparametric regression models with predictors being measured with a mixture of Berkson and classical errors. In practice, the Berkson error arises when the variable X of interest is uno...We consider the estimation of nonparametric regression models with predictors being measured with a mixture of Berkson and classical errors. In practice, the Berkson error arises when the variable X of interest is unobservable and only a proxy of X can be measured while the inaccuracy related to the observation of the proxy causes an error of classical type. In this paper, we propose two nonparametric estimators of the regression function in the presence of either or both types of errors. We prove the asymptotic normality of our estimators and derive their rates of convergence. The finite-sample properties of the estimators are investigated through simulation studies.展开更多
This paper proposes a steady-state errors correction(SSEC)method for eliminating measurement errors.This method is based on the detections of error signal E(s)and output C(s)which generate an expected output R(s).In c...This paper proposes a steady-state errors correction(SSEC)method for eliminating measurement errors.This method is based on the detections of error signal E(s)and output C(s)which generate an expected output R(s).In comparison with the conventional solutions which are based on detecting the expected output R(s)and output C(s)to obtain error signal E(s),the measurement errors are eliminated even the error might be at a significant level.Moreover,it is possible that the individual debugging by regulating the coefficient K for every member of the multiple objectives achieves the optimization of the open loop gain.Therefore,this simple method can be applied to the weak coupling and multiple objectives system,which is usually controlled by complex controller.The principle of eliminating measurement errors is derived analytically,and the advantages comparing with the conventional solutions are depicted.Based on the SSEC method analysis,an application of this method for an active power filter(APF)is investigated and the effectiveness and viability of the scheme are demonstrated through the simulation and experimental verifications.展开更多
Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degrad...Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item's individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.展开更多
For high-dimensional models with a focus on classification performance,the?1-penalized logistic regression is becoming important and popular.However,the Lasso estimates could be problematic when penalties of different...For high-dimensional models with a focus on classification performance,the?1-penalized logistic regression is becoming important and popular.However,the Lasso estimates could be problematic when penalties of different coefficients are all the same and not related to the data.We propose two types of weighted Lasso estimates,depending upon covariates determined by the Mc Diarmid inequality.Given sample size n and a dimension of covariates p,the finite sample behavior of our proposed method with a diverging number of predictors is illustrated by non-asymptotic oracle inequalities such as the?1-estimation error and the squared prediction error of the unknown parameters.We compare the performance of our method with that of former weighted estimates on simulated data,then apply it to do real data analysis.展开更多
Nonadiabatic holonomic quantum computers serve as the physical platform for nonadiabatic holonomic quantum computation.As quantum computation has entered the noisy intermediate-scale era,building accurate intermediate...Nonadiabatic holonomic quantum computers serve as the physical platform for nonadiabatic holonomic quantum computation.As quantum computation has entered the noisy intermediate-scale era,building accurate intermediate-scale nonadiabatic holo-nomic quantum computers is clearly necessary.Given that measurements are the sole means of extracting information,they play an indispensable role in nonadiabatic holonomic quantum computers.Accordingly,developing methods to reduce measurement errors in nonadiabatic holonomic quantum computers is of great importance.However,while much attention has been given to the research on nonadiabatic holonomic gates,the research on reducing measurement errors in nonadiabatic holonomic quantum computers is severely lacking.In this study,we propose a measurement error reduction method tailored for intermediate-scale nonadiabatic holonomic quantum computers.The reason we say this is because our method can not only reduce the measurement errors in the computer but also be useful in mitigating errors originating from nonadiabatic holonomic gates.Given these features,our method significantly advances the construction of accurate intermediate-scale nonadiabatic holonomic quantum computers.展开更多
In order to discover the range of various errors in Chinese precipitation measurements and seek a correction method, 30 precipitation evaluation stations were set up countrywide before 1993. All the stations are refer...In order to discover the range of various errors in Chinese precipitation measurements and seek a correction method, 30 precipitation evaluation stations were set up countrywide before 1993. All the stations are reference stations in China. To seek a correction method for wind-induced error, a precipitation correction instrument called the ＂horizontal precipitation gauge＂ was devised beforehand. Field intercomparison observations regarding 29,000 precipitation events have been conducted using one pit gauge, two elevated operational gauges and one horizontal gauge at the above 30 stations. The range of precipitation measurement errors in China is obtained by analysis of intercomparison measurement results. The distribution of random errors and systematic errors in precipitation measurements are studied in this paper. A correction method, especially for wind-induced errors, is developed. The results prove that a correlation of power function exists between the precipitation amount caught by the horizontal gauge and the absolute difference of observations implemented by the operational gauge and pit gauge. The correlation coefficient is 0.99. For operational observations, precipitation correction can be carried out only by parallel observation with a horizontal precipitation gauge. The precipitation accuracy after correction approaches that of the pit gauge. The correction method developed is simple and feasible.展开更多
Influence of temperature on measurement of surface plasmon resonance （SPR） sensor was investigated. Samples with various concentrations of NaCl were tested at different temperatures. It was shown that if the affecti...Influence of temperature on measurement of surface plasmon resonance （SPR） sensor was investigated. Samples with various concentrations of NaCl were tested at different temperatures. It was shown that if the affection of temperature could be neglected, measurement precision of salt solution was 0.028 wt.-%. But measurement error of salinity caused by temperature was 0.53 wt.-% in average when the temperature drift was 1 ℃. To reduce the error, a double-cell SPR sensor with salt solution and distilled water flowing respectively and at the same temperature was implemented.展开更多
The Wiener process as a degradation model plays an important role in the degradation analysis.In this paper, we propose an objective Bayesian analysis for an acceleration degradation Wienermodel which is subjected to ...The Wiener process as a degradation model plays an important role in the degradation analysis.In this paper, we propose an objective Bayesian analysis for an acceleration degradation Wienermodel which is subjected to measurement errors. The Jeffreys prior and reference priors underdifferent group orderings are first derived, the propriety of the posteriors is then validated. It isshown that two of the reference priors can yield proper posteriors while the others cannot. A simulation study is carried out to investigate the frequentist performance of the approach comparedto the maximum likelihood method. Finally, the approach is applied to analyse a real data.展开更多
The linear mixed-effects model （LMM） is a very useful tool for analyzing cluster data. In practice, however, the exact values of the variables are often difficult to observe. In this paper, we consider the LMM with ...The linear mixed-effects model （LMM） is a very useful tool for analyzing cluster data. In practice, however, the exact values of the variables are often difficult to observe. In this paper, we consider the LMM with measurement errors in the covariates. The empirical BLUP estimator of the linear combination of the fixed and random effects and its approximate conditional MSE are derived. The application to the estimation of small area is provided. Simulation study shows good performance of the proposed estimators.展开更多
The measurement errors due to nonparallelness of specimen faces in the ultrasonic velocity and attenuation coefficient measured by the pulse reflection method in VHF range have been investigated theoretically, and the...The measurement errors due to nonparallelness of specimen faces in the ultrasonic velocity and attenuation coefficient measured by the pulse reflection method in VHF range have been investigated theoretically, and the theoretical expressions for estimating these measurement errors are given. It has also been shown that, the attenuation coefficient error is depending on both the nonparallelness angle of specimen faces and the ultrasonic frequency, but the velocity error is only depending on the former. Furthermore, for pure silica glass specimen it is estimated that, in VHF range in order to insure that the attenuation coefficient and velocity errors due to nonparallelness of specimen faces are less than 10% and 0.01%, respectively, the nonparallelness angle of specimen faces must be less than 10 s and 40 s correspondingly.展开更多
In this paper the Kiefer-Wolfowitz (KW) procedure for searching the extremum of the regression function as well as the Robbins-Monro (RM) procedure for solving the regression equation are modified in order that they c...In this paper the Kiefer-Wolfowitz (KW) procedure for searching the extremum of the regression function as well as the Robbins-Monro (RM) procedure for solving the regression equation are modified in order that they can be applied to the case when the measurement errors form an ARMA process. Simple conditions are given to guarantee their convergence to the extremum and the root of regression function respectively by using a new approach combining both the probabilistic method and the ordinary differential equation (ODE) method. The results given here are better than the well-known ones even if the measurement error is the martingale difference sequence.展开更多
In this paper,the authors investigate three aspects of statistical inference for the partially linear regression models where some covariates are measured with errors.Firstly, a bandwidth selection procedure is propos...In this paper,the authors investigate three aspects of statistical inference for the partially linear regression models where some covariates are measured with errors.Firstly, a bandwidth selection procedure is proposed,which is a combination of the differencebased technique and GCV method.Secondly,a goodness-of-fit test procedure is proposed, which is an extension of the generalized likelihood technique.Thirdly,a variable selection procedure for the parametric part is provided based on the nonconcave penalization and corrected profile least squares.Same as＂Variable selection via nonconcave penalized likelihood and its oracle properties＂（J.Amer.Statist.Assoc.,96,2001,1348-1360）,it is shown that the resulting estimator has an oracle property with a proper choice of regularization parameters and penalty function.Simulation studies are conducted to illustrate the finite sample performances of the proposed procedures.展开更多
Runoff plots are widely used worldwide to monitor water and soil losses.Sediment concentration in runoff collection tank is measured by stirring-sampling procedure,but this method may produce high measurement error du...Runoff plots are widely used worldwide to monitor water and soil losses.Sediment concentration in runoff collection tank is measured by stirring-sampling procedure,but this method may produce high measurement error due to the uneven mixing of collected sediments with water and soil particle deposition.This study aimed to identify the relationship between actual and measured sediment concentrations,so as to estimate the systematic error of sediment concentration measurement from runoff collection tank by traditional stirring-sampling procedure and the possibility to eliminate it.Four major soils including black soil,silt loess,clay loess,and purple soil in China were used to determine the correlation between the measured and designed sediment concentrations in laboratory.Tested sediment concentration was 1,2,5,8,10,20,50,80,100,200,500,800,and 1000 kg/m^(3),and total sediment-laden water volume was 50 L and 100 L.Five samples were collected successively from collection tank for each treatment and their sediment concentrations were measured by conventional oven-drying method.The results showed that all the measured sediment concentration values were smaller than the designed ones,but both the measured and designed values were linearly correlated significantly with determination coefficients greater than 0.8,generally.In the whole tested concentration range,the systematical error was-0.19 to-319.95 kg/m^(3) and relative error was 0.30%-84.5% for the 4 tested soils and 2 total sediment-laden water volumes.These results indicated a necessity and possibility to correct conventional sediment concentration measurement value.The result is usable to assess and correct the measurement error of sediment concentrations from traditional runoff plot.展开更多
Aims Accurate forecast of ecosystem states is critical for improving natural resourcemanagement and climate change mitigation.Assimilating observed data into models is an effective way to reduce uncertainties in ecolo...Aims Accurate forecast of ecosystem states is critical for improving natural resourcemanagement and climate change mitigation.Assimilating observed data into models is an effective way to reduce uncertainties in ecological forecasting.However,influences ofmeasurement errors on parameter estimation and forecasted state changes have not been carefully examined.This study analyzed the parameter identifiability of a process-based ecosystem carbon cycle model,the sensitivity of parameter estimates and model forecasts to the magnitudes of measurement errors and the information contributions of the assimilated data to model forecasts with a data assimilation approach.Methods We applied a Markov Chain Monte Carlo method to assimilate eight biometric data sets into the Terrestrial ECOsystemmodel.The data were the observations of foliage biomass,wood biomass,fine root biomass,microbial biomass,litter fall,litter,soil carbon and soil respiration,collected at the Duke Forest free-air CO_(2)enrichment facilities from 1996 to 2005.Three levels ofmeasurement errorswere assigned to these data sets by halving and doubling their original standard deviations.Important Findings Results showed that only less than half of the 30 parameters could be constrained,though the observations were extensive and themodelwas relatively simple.Highermeasurement errors led to higher uncertainties in parameters estimates and forecasted carbon(C)pool sizes.The longterm predictions of the slow turnover pools were affected less by the measurement errors than those of fast turnover pools.Assimilated data contributed less information for the pools with long residence times in long-term forecasts.These results indicate the residence times of C pools played a key role in regulating propagation of errors from measurements to model forecasts in a data assimilation system.Improving the estimation of parameters of slowturnover C pools is the key to better forecast long-term ecosystem C dynamics.展开更多
In this paper,an antenna array composed of circular array and orthogonal linear array is proposed by using the design of long and short baseline“orthogonal linear array”and the circular array ambiguity resolution de...In this paper,an antenna array composed of circular array and orthogonal linear array is proposed by using the design of long and short baseline“orthogonal linear array”and the circular array ambiguity resolution design of multi-group baseline clustering.The effectiveness of the antenna array in this paper is verified by sufficient simulation and experiment.After the system deviation correction work,it is found that in the L/S/C/X frequency bands,the ambiguity resolution probability is high,and the phase difference system error between each channel is basically the same.The angle measurement error is less than 0.5°,and the positioning error is less than 2.5 km.Notably,as the center frequency increases,calibration consistency improves,and the calibration frequency points become applicable over a wider frequency range.At a center frequency of 11.5 GHz,the calibration frequency point bandwidth extends to 1200 MHz.This combined antenna array deployment holds significant promise for a wide range of applications in contemporary wireless communication systems.展开更多
This paper is concerned with the estimating problem of a semiparametric varying-coefficient partially linear errors-in-variables model Yi=Xτiβ＋Zτiα（Ui）＋εi , Wi=Xi＋ξi,i=1, · · · , n. Due to me...This paper is concerned with the estimating problem of a semiparametric varying-coefficient partially linear errors-in-variables model Yi=Xτiβ＋Zτiα（Ui）＋εi , Wi=Xi＋ξi,i=1, · · · , n. Due to measurement errors, the usual profile least square estimator of the parametric component, local polynomial estimator of the nonparametric component and profile least squares based estimator of the error variance are biased and inconsistent. By taking the measurement errors into account we propose a generalized profile least squares estimator for the parametric component and show it is consistent and asymptotically normal. Correspondingly, the consistent estimation of the nonparametric component and error variance are proposed as well. These results may be used to make asymptotically valid statistical inferences. Some simulation studies are conducted to illustrate the finite sample performance of these proposed estimations.展开更多
Stirring-sampling method is a widely adopted method to measure sediment concentrations in collection tanks of runoff plots,but with high systematic measurement errors.This research aimed to advance an approach for bui...Stirring-sampling method is a widely adopted method to measure sediment concentrations in collection tanks of runoff plots,but with high systematic measurement errors.This research aimed to advance an approach for building correction equations to remove measurement errors in designed sediment concentration range.Experimental data of sediment measurement from the stirring-sampling method,with four representative soils,under the designed sediment concentrations(1,2,5,8,10,20,50,80,100,200,500,800,and 1000 kg/m^(3))were used to demonstrate the correction methodological process.Two correction methods(step-wise correction and universal correction)were suggested for the trial in this study based on the distribution of measurement errors.In the step-wise correction,the correction equations were made with a series of linear functions without intercept for the low concentration group(0-20 kg/m^(3)),a series of linear functions with intercept for the high(20-200 kg/m^(3))and extremely high(200-1000 kg/m^(3))concentration groups,consecutively.The correction equations were a series of power functions in the universal correction.For the step-wise correction,most of the relative errors of correction sediment concentrations were smaller than 15%and 10%under high and extremely high concentration groups,but the corrected accuracy was not good in the sediment concentration of 1,2,5 kg/m^(3)with the corrected relative errors of 0.20%-206.07%.For the universal correction,the corrected relative errors(0.19%-31.81%)of the four soils were low under the condition of extremely high sediment concentrations,but other corrected accuracies weren’t good with the corrected relative errors of 0.68%-1154.71%.The corrected accuracy of step-wise correction is higher than that of the universal correction,but the universal correction is more convenient.These results indicated that the correction equations could efficiently revise the measurement errors of the tested soils and that this method can be generalized to other soil types and was meaningful in monitoring soil erosion.展开更多
The assessment of the measurement error status of online Capacitor Voltage Transformers (CVT) within the power grid is of profound significance to the equitable trade of electric energy and the secure operation of the...The assessment of the measurement error status of online Capacitor Voltage Transformers (CVT) within the power grid is of profound significance to the equitable trade of electric energy and the secure operation of the power grid. This paper advances an online CVT error state evaluation method, anchored in the in-phase relationship and outlier detection. Initially, this method leverages the in-phase relationship to obviate the influence of primary side fluctuations in the grid on assessment accuracy. Subsequently, Principal Component Analysis (PCA) is employed to meticulously disentangle the error change information inherent in the CVT from the measured values and to compute statistics that delineate the error state. Finally, the Local Outlier Factor (LOF) is deployed to discern outliers in the statistics, with thresholds serving to appraise the CVT error state. Experimental results incontrovertibly demonstrate the efficacy of this method, showcasing its prowess in effecting online tracking of CVT error changes and conducting error state assessments. The discernible enhancements in reliability, accuracy, and sensitivity are manifest, with the assessment accuracy reaching an exemplary 0.01%.展开更多
In this paper,we propose a roll angle measurement method with a large range based on the photoelectronic autocollimator.According to the corresponding relationship between the rotation position of the measured shaft a...In this paper,we propose a roll angle measurement method with a large range based on the photoelectronic autocollimator.According to the corresponding relationship between the rotation position of the measured shaft and the spot position on the circular trajectory,the roll angle is calculated quickly and conveniently using a simple algorithm.Only a mirror,a coupler and a fine shaft are contained in the measurement system besides the photoelectronic autocollimator.Aiming at the terrible measurement error induced by the axis wobbly error,two measurement schemes are proposed,which are linking the fine precision shaft to the measured shaft for reducing the axis wobbly error and using the segment measurement to enlarge the radius of the circular trajectory.The experimental results show that the measurement error is decreased by ±0.38°.The roll angle error of the mechanism is ±0.14°,and the measurement precision is about ±2′.The proposed method can be widely used in the engineering fields.展开更多
Some electrical parameters of the SIS-type hysteretic underdamped Josephson junction(JJ)can be measured by its current-voltage characteristics(IVCs).Currents and voltages at JJ are commensurate with the intrinsic nois...Some electrical parameters of the SIS-type hysteretic underdamped Josephson junction(JJ)can be measured by its current-voltage characteristics(IVCs).Currents and voltages at JJ are commensurate with the intrinsic noise level of measuring instruments.This leads to the need for multiple measurements with subsequent statistical processing.In this paper,the digital algorithms are proposed for the automatic measurement of the JJ parameters by IVC.These algorithms make it possible to implement multiple measurements and check these JJ parameters in an automatic mode with the required accuracy.The complete sufficient statistics are used to minimize the root-mean-square error of parameter measurement.A sequence of current pulses with slow rising and falling edges is used to drive JJ,and synchronous current and voltage readings at JJ are used to realize measurement algorithms.The algorithm performance is estimated through computer simulations.The significant advantage of the proposed algorithms is the independence from current source noise and intrinsic noise of current and voltage meters,as well as the simple implementation in automatic digital measuring systems.The proposed algorithms can be used to control JJ parameters during mass production of superconducting integrated circuits,which will improve the production efficiency and product quality.展开更多
文摘We consider the estimation of nonparametric regression models with predictors being measured with a mixture of Berkson and classical errors. In practice, the Berkson error arises when the variable X of interest is unobservable and only a proxy of X can be measured while the inaccuracy related to the observation of the proxy causes an error of classical type. In this paper, we propose two nonparametric estimators of the regression function in the presence of either or both types of errors. We prove the asymptotic normality of our estimators and derive their rates of convergence. The finite-sample properties of the estimators are investigated through simulation studies.
基金National Natural Science Foundation of China(No.61273172)
文摘This paper proposes a steady-state errors correction(SSEC)method for eliminating measurement errors.This method is based on the detections of error signal E(s)and output C(s)which generate an expected output R(s).In comparison with the conventional solutions which are based on detecting the expected output R(s)and output C(s)to obtain error signal E(s),the measurement errors are eliminated even the error might be at a significant level.Moreover,it is possible that the individual debugging by regulating the coefficient K for every member of the multiple objectives achieves the optimization of the open loop gain.Therefore,this simple method can be applied to the weak coupling and multiple objectives system,which is usually controlled by complex controller.The principle of eliminating measurement errors is derived analytically,and the advantages comparing with the conventional solutions are depicted.Based on the SSEC method analysis,an application of this method for an active power filter(APF)is investigated and the effectiveness and viability of the scheme are demonstrated through the simulation and experimental verifications.
基金Projects(51475462,61374138,61370031)supported by the National Natural Science Foundation of China
文摘Real time remaining useful life(RUL) prediction based on condition monitoring is an essential part in condition based maintenance(CBM). In the current methods about the real time RUL prediction of the nonlinear degradation process, the measurement error is not considered and forecasting uncertainty is large. Therefore, an approximate analytical RUL distribution in a closed-form of a nonlinear Wiener based degradation process with measurement errors was proposed. The maximum likelihood estimation approach was used to estimate the unknown fixed parameters in the proposed model. When the newly observed data are available, the random parameter is updated by the Bayesian method to make the estimation adapt to the item's individual characteristic and reduce the uncertainty of the estimation. The simulation results show that considering measurement errors in the degradation process can significantly improve the accuracy of real time RUL prediction.
基金Supported by the National Natural Science Foundation of China(61877023)the Fundamental Research Funds for the Central Universities(CCNU19TD009)。
文摘For high-dimensional models with a focus on classification performance,the?1-penalized logistic regression is becoming important and popular.However,the Lasso estimates could be problematic when penalties of different coefficients are all the same and not related to the data.We propose two types of weighted Lasso estimates,depending upon covariates determined by the Mc Diarmid inequality.Given sample size n and a dimension of covariates p,the finite sample behavior of our proposed method with a diverging number of predictors is illustrated by non-asymptotic oracle inequalities such as the?1-estimation error and the squared prediction error of the unknown parameters.We compare the performance of our method with that of former weighted estimates on simulated data,then apply it to do real data analysis.
基金supported by the National Natural Science Foundation of China(Grant No.12174224)。
文摘Nonadiabatic holonomic quantum computers serve as the physical platform for nonadiabatic holonomic quantum computation.As quantum computation has entered the noisy intermediate-scale era,building accurate intermediate-scale nonadiabatic holo-nomic quantum computers is clearly necessary.Given that measurements are the sole means of extracting information,they play an indispensable role in nonadiabatic holonomic quantum computers.Accordingly,developing methods to reduce measurement errors in nonadiabatic holonomic quantum computers is of great importance.However,while much attention has been given to the research on nonadiabatic holonomic gates,the research on reducing measurement errors in nonadiabatic holonomic quantum computers is severely lacking.In this study,we propose a measurement error reduction method tailored for intermediate-scale nonadiabatic holonomic quantum computers.The reason we say this is because our method can not only reduce the measurement errors in the computer but also be useful in mitigating errors originating from nonadiabatic holonomic gates.Given these features,our method significantly advances the construction of accurate intermediate-scale nonadiabatic holonomic quantum computers.
文摘In order to discover the range of various errors in Chinese precipitation measurements and seek a correction method, 30 precipitation evaluation stations were set up countrywide before 1993. All the stations are reference stations in China. To seek a correction method for wind-induced error, a precipitation correction instrument called the ＂horizontal precipitation gauge＂ was devised beforehand. Field intercomparison observations regarding 29,000 precipitation events have been conducted using one pit gauge, two elevated operational gauges and one horizontal gauge at the above 30 stations. The range of precipitation measurement errors in China is obtained by analysis of intercomparison measurement results. The distribution of random errors and systematic errors in precipitation measurements are studied in this paper. A correction method, especially for wind-induced errors, is developed. The results prove that a correlation of power function exists between the precipitation amount caught by the horizontal gauge and the absolute difference of observations implemented by the operational gauge and pit gauge. The correlation coefficient is 0.99. For operational observations, precipitation correction can be carried out only by parallel observation with a horizontal precipitation gauge. The precipitation accuracy after correction approaches that of the pit gauge. The correction method developed is simple and feasible.
基金This work was supported by the Shu Guang Project of Shanghai Education Committee (No. 02SG32)the Shanghai Leading Academic Discipline Project (No.T0501).
文摘Influence of temperature on measurement of surface plasmon resonance （SPR） sensor was investigated. Samples with various concentrations of NaCl were tested at different temperatures. It was shown that if the affection of temperature could be neglected, measurement precision of salt solution was 0.028 wt.-%. But measurement error of salinity caused by temperature was 0.53 wt.-% in average when the temperature drift was 1 ℃. To reduce the error, a double-cell SPR sensor with salt solution and distilled water flowing respectively and at the same temperature was implemented.
基金The work is supported by the Humanities and Social Sciences Foundation of Ministry of Education,China(Grant No.17YJC910003).
文摘The Wiener process as a degradation model plays an important role in the degradation analysis.In this paper, we propose an objective Bayesian analysis for an acceleration degradation Wienermodel which is subjected to measurement errors. The Jeffreys prior and reference priors underdifferent group orderings are first derived, the propriety of the posteriors is then validated. It isshown that two of the reference priors can yield proper posteriors while the others cannot. A simulation study is carried out to investigate the frequentist performance of the approach comparedto the maximum likelihood method. Finally, the approach is applied to analyse a real data.
基金supported by National Natural Science Foundation of China(Grant No.11301514)partially supported by National Natural Science Foundation of China(Grant Nos.11271355 and 70625004)National Bureau of Statistics of China(Grant No.2012LZ012)
文摘The linear mixed-effects model （LMM） is a very useful tool for analyzing cluster data. In practice, however, the exact values of the variables are often difficult to observe. In this paper, we consider the LMM with measurement errors in the covariates. The empirical BLUP estimator of the linear combination of the fixed and random effects and its approximate conditional MSE are derived. The application to the estimation of small area is provided. Simulation study shows good performance of the proposed estimators.
文摘The measurement errors due to nonparallelness of specimen faces in the ultrasonic velocity and attenuation coefficient measured by the pulse reflection method in VHF range have been investigated theoretically, and the theoretical expressions for estimating these measurement errors are given. It has also been shown that, the attenuation coefficient error is depending on both the nonparallelness angle of specimen faces and the ultrasonic frequency, but the velocity error is only depending on the former. Furthermore, for pure silica glass specimen it is estimated that, in VHF range in order to insure that the attenuation coefficient and velocity errors due to nonparallelness of specimen faces are less than 10% and 0.01%, respectively, the nonparallelness angle of specimen faces must be less than 10 s and 40 s correspondingly.
文摘In this paper the Kiefer-Wolfowitz (KW) procedure for searching the extremum of the regression function as well as the Robbins-Monro (RM) procedure for solving the regression equation are modified in order that they can be applied to the case when the measurement errors form an ARMA process. Simple conditions are given to guarantee their convergence to the extremum and the root of regression function respectively by using a new approach combining both the probabilistic method and the ordinary differential equation (ODE) method. The results given here are better than the well-known ones even if the measurement error is the martingale difference sequence.
文摘In this paper,the authors investigate three aspects of statistical inference for the partially linear regression models where some covariates are measured with errors.Firstly, a bandwidth selection procedure is proposed,which is a combination of the differencebased technique and GCV method.Secondly,a goodness-of-fit test procedure is proposed, which is an extension of the generalized likelihood technique.Thirdly,a variable selection procedure for the parametric part is provided based on the nonconcave penalization and corrected profile least squares.Same as＂Variable selection via nonconcave penalized likelihood and its oracle properties＂（J.Amer.Statist.Assoc.,96,2001,1348-1360）,it is shown that the resulting estimator has an oracle property with a proper choice of regularization parameters and penalty function.Simulation studies are conducted to illustrate the finite sample performances of the proposed procedures.
基金This work was financially supported by the“National Key Research and Development Program of China”under Project No.2016YFC0502403the“National Natural Science Foundation of China”under Project No.41230746 and No.51621061.
文摘Runoff plots are widely used worldwide to monitor water and soil losses.Sediment concentration in runoff collection tank is measured by stirring-sampling procedure,but this method may produce high measurement error due to the uneven mixing of collected sediments with water and soil particle deposition.This study aimed to identify the relationship between actual and measured sediment concentrations,so as to estimate the systematic error of sediment concentration measurement from runoff collection tank by traditional stirring-sampling procedure and the possibility to eliminate it.Four major soils including black soil,silt loess,clay loess,and purple soil in China were used to determine the correlation between the measured and designed sediment concentrations in laboratory.Tested sediment concentration was 1,2,5,8,10,20,50,80,100,200,500,800,and 1000 kg/m^(3),and total sediment-laden water volume was 50 L and 100 L.Five samples were collected successively from collection tank for each treatment and their sediment concentrations were measured by conventional oven-drying method.The results showed that all the measured sediment concentration values were smaller than the designed ones,but both the measured and designed values were linearly correlated significantly with determination coefficients greater than 0.8,generally.In the whole tested concentration range,the systematical error was-0.19 to-319.95 kg/m^(3) and relative error was 0.30%-84.5% for the 4 tested soils and 2 total sediment-laden water volumes.These results indicated a necessity and possibility to correct conventional sediment concentration measurement value.The result is usable to assess and correct the measurement error of sediment concentrations from traditional runoff plot.
基金This research was financially supported by the Office of Science(BER),Department of Energy(DE-FG02-006ER64319)through the Midwestern Regional Center of the National Institute for Climatic Change Research at Michigan Technological University,under Award Number DE-FC02-06ER64158by National Science Foundation(DEB0078325 andDEB0743778).Themodel runswere performed at the Supercomputing Center for Education&Research(OSCER),University of Oklahoma.
文摘Aims Accurate forecast of ecosystem states is critical for improving natural resourcemanagement and climate change mitigation.Assimilating observed data into models is an effective way to reduce uncertainties in ecological forecasting.However,influences ofmeasurement errors on parameter estimation and forecasted state changes have not been carefully examined.This study analyzed the parameter identifiability of a process-based ecosystem carbon cycle model,the sensitivity of parameter estimates and model forecasts to the magnitudes of measurement errors and the information contributions of the assimilated data to model forecasts with a data assimilation approach.Methods We applied a Markov Chain Monte Carlo method to assimilate eight biometric data sets into the Terrestrial ECOsystemmodel.The data were the observations of foliage biomass,wood biomass,fine root biomass,microbial biomass,litter fall,litter,soil carbon and soil respiration,collected at the Duke Forest free-air CO_(2)enrichment facilities from 1996 to 2005.Three levels ofmeasurement errorswere assigned to these data sets by halving and doubling their original standard deviations.Important Findings Results showed that only less than half of the 30 parameters could be constrained,though the observations were extensive and themodelwas relatively simple.Highermeasurement errors led to higher uncertainties in parameters estimates and forecasted carbon(C)pool sizes.The longterm predictions of the slow turnover pools were affected less by the measurement errors than those of fast turnover pools.Assimilated data contributed less information for the pools with long residence times in long-term forecasts.These results indicate the residence times of C pools played a key role in regulating propagation of errors from measurements to model forecasts in a data assimilation system.Improving the estimation of parameters of slowturnover C pools is the key to better forecast long-term ecosystem C dynamics.
文摘In this paper,an antenna array composed of circular array and orthogonal linear array is proposed by using the design of long and short baseline“orthogonal linear array”and the circular array ambiguity resolution design of multi-group baseline clustering.The effectiveness of the antenna array in this paper is verified by sufficient simulation and experiment.After the system deviation correction work,it is found that in the L/S/C/X frequency bands,the ambiguity resolution probability is high,and the phase difference system error between each channel is basically the same.The angle measurement error is less than 0.5°,and the positioning error is less than 2.5 km.Notably,as the center frequency increases,calibration consistency improves,and the calibration frequency points become applicable over a wider frequency range.At a center frequency of 11.5 GHz,the calibration frequency point bandwidth extends to 1200 MHz.This combined antenna array deployment holds significant promise for a wide range of applications in contemporary wireless communication systems.
基金supported by National Natural Science Funds for Distinguished Young Scholar(No.70825004) and (No.71271128)Creative Research Groups of China(No.71271128)+1 种基金NCMIS and Shanghai University of Finance and Economics through Project 211 Phase ⅢShanghai Leading Academic Discipline Project(No.B803)
文摘This paper is concerned with the estimating problem of a semiparametric varying-coefficient partially linear errors-in-variables model Yi=Xτiβ＋Zτiα（Ui）＋εi , Wi=Xi＋ξi,i=1, · · · , n. Due to measurement errors, the usual profile least square estimator of the parametric component, local polynomial estimator of the nonparametric component and profile least squares based estimator of the error variance are biased and inconsistent. By taking the measurement errors into account we propose a generalized profile least squares estimator for the parametric component and show it is consistent and asymptotically normal. Correspondingly, the consistent estimation of the nonparametric component and error variance are proposed as well. These results may be used to make asymptotically valid statistical inferences. Some simulation studies are conducted to illustrate the finite sample performance of these proposed estimations.
基金supported by the“National Key Research and Development Program of China”under Project No.2016YFC0502403the“National Natural Science Foundation of China”under Project No.41230746,No.51621061.
文摘Stirring-sampling method is a widely adopted method to measure sediment concentrations in collection tanks of runoff plots,but with high systematic measurement errors.This research aimed to advance an approach for building correction equations to remove measurement errors in designed sediment concentration range.Experimental data of sediment measurement from the stirring-sampling method,with four representative soils,under the designed sediment concentrations(1,2,5,8,10,20,50,80,100,200,500,800,and 1000 kg/m^(3))were used to demonstrate the correction methodological process.Two correction methods(step-wise correction and universal correction)were suggested for the trial in this study based on the distribution of measurement errors.In the step-wise correction,the correction equations were made with a series of linear functions without intercept for the low concentration group(0-20 kg/m^(3)),a series of linear functions with intercept for the high(20-200 kg/m^(3))and extremely high(200-1000 kg/m^(3))concentration groups,consecutively.The correction equations were a series of power functions in the universal correction.For the step-wise correction,most of the relative errors of correction sediment concentrations were smaller than 15%and 10%under high and extremely high concentration groups,but the corrected accuracy was not good in the sediment concentration of 1,2,5 kg/m^(3)with the corrected relative errors of 0.20%-206.07%.For the universal correction,the corrected relative errors(0.19%-31.81%)of the four soils were low under the condition of extremely high sediment concentrations,but other corrected accuracies weren’t good with the corrected relative errors of 0.68%-1154.71%.The corrected accuracy of step-wise correction is higher than that of the universal correction,but the universal correction is more convenient.These results indicated that the correction equations could efficiently revise the measurement errors of the tested soils and that this method can be generalized to other soil types and was meaningful in monitoring soil erosion.
文摘The assessment of the measurement error status of online Capacitor Voltage Transformers (CVT) within the power grid is of profound significance to the equitable trade of electric energy and the secure operation of the power grid. This paper advances an online CVT error state evaluation method, anchored in the in-phase relationship and outlier detection. Initially, this method leverages the in-phase relationship to obviate the influence of primary side fluctuations in the grid on assessment accuracy. Subsequently, Principal Component Analysis (PCA) is employed to meticulously disentangle the error change information inherent in the CVT from the measured values and to compute statistics that delineate the error state. Finally, the Local Outlier Factor (LOF) is deployed to discern outliers in the statistics, with thresholds serving to appraise the CVT error state. Experimental results incontrovertibly demonstrate the efficacy of this method, showcasing its prowess in effecting online tracking of CVT error changes and conducting error state assessments. The discernible enhancements in reliability, accuracy, and sensitivity are manifest, with the assessment accuracy reaching an exemplary 0.01%.
基金supported by the National Natural Science Foundation of China(Nos.111742741117427961205021 and 11204299)
文摘In this paper,we propose a roll angle measurement method with a large range based on the photoelectronic autocollimator.According to the corresponding relationship between the rotation position of the measured shaft and the spot position on the circular trajectory,the roll angle is calculated quickly and conveniently using a simple algorithm.Only a mirror,a coupler and a fine shaft are contained in the measurement system besides the photoelectronic autocollimator.Aiming at the terrible measurement error induced by the axis wobbly error,two measurement schemes are proposed,which are linking the fine precision shaft to the measured shaft for reducing the axis wobbly error and using the segment measurement to enlarge the radius of the circular trajectory.The experimental results show that the measurement error is decreased by ±0.38°.The roll angle error of the mechanism is ±0.14°,and the measurement precision is about ±2′.The proposed method can be widely used in the engineering fields.
基金the Ministry of Science and Higher Education of the Russian Federation under Grant No.FSUN-2023-0007.
文摘Some electrical parameters of the SIS-type hysteretic underdamped Josephson junction(JJ)can be measured by its current-voltage characteristics(IVCs).Currents and voltages at JJ are commensurate with the intrinsic noise level of measuring instruments.This leads to the need for multiple measurements with subsequent statistical processing.In this paper,the digital algorithms are proposed for the automatic measurement of the JJ parameters by IVC.These algorithms make it possible to implement multiple measurements and check these JJ parameters in an automatic mode with the required accuracy.The complete sufficient statistics are used to minimize the root-mean-square error of parameter measurement.A sequence of current pulses with slow rising and falling edges is used to drive JJ,and synchronous current and voltage readings at JJ are used to realize measurement algorithms.The algorithm performance is estimated through computer simulations.The significant advantage of the proposed algorithms is the independence from current source noise and intrinsic noise of current and voltage meters,as well as the simple implementation in automatic digital measuring systems.The proposed algorithms can be used to control JJ parameters during mass production of superconducting integrated circuits,which will improve the production efficiency and product quality.
