In this paper, we define the Weibull kernel and use it to nonparametric estimation of the probability density function (pdf) and the hazard rate function for independent and identically distributed (iid) data. The bia...In this paper, we define the Weibull kernel and use it to nonparametric estimation of the probability density function (pdf) and the hazard rate function for independent and identically distributed (iid) data. The bias, variance and the optimal bandwidth of the proposed estimator are investigated. Moreover, the asymptotic normality of the proposed estimator is investigated. The performance of the proposed estimator is tested using simulation study and real data.展开更多
In this paper, the normal approximation rate and the random weighting approximation rate of error distribution of the kernel estimator of conditional density function f(y|x) are studied. The results may be used to...In this paper, the normal approximation rate and the random weighting approximation rate of error distribution of the kernel estimator of conditional density function f(y|x) are studied. The results may be used to construct the confidence interval of f(y|x) .展开更多
In this paper two kernel density estimators are introduced and investigated. In order to reduce bias, we intuitively subtract an estimated bias term from ordinary kernel density estimator. The second proposed density ...In this paper two kernel density estimators are introduced and investigated. In order to reduce bias, we intuitively subtract an estimated bias term from ordinary kernel density estimator. The second proposed density estimator is a geometric extrapolation of the first bias reduced estimator. Theoretical properties such as bias, variance and mean squared error are investigated for both estimators. To observe their finite sample performance, a Monte Carlo simulation study based on small to moderately large samples is presented.展开更多
The filling rate and the starch accumulation in developing maize kernel were analyzed. The changes of enzyme activities associated with sucrose metabolism and starch biosynthesis were investigated. The purpose is to d...The filling rate and the starch accumulation in developing maize kernel were analyzed. The changes of enzyme activities associated with sucrose metabolism and starch biosynthesis were investigated. The purpose is to discuss the enzymatic mechanisms responsible for starch synthesis. Two types of maize cultivars （Zea mays）, high starch maize （Feiyu 3） and normal maize （Yuyu 22）, were grown in a corn field. The factors involved in starch synthesis were performed during the growth period. The kernel filling rate, the sucrose content, the starch accumulating rates and the activities of SS （sucrose synthase）, GBSS （granule-bound starch synthase）, SBE （starch branching enzyme） of Feiyu 3, which has high starch content, were significantly higher than those of Yuyu 22, which has low starch content, after 10 DAP （days after pollination）. Correlation analysis indicated that ADPGPPase （ADP-glucose pyrophosphorylase） and DBE （starch debranching enzyme） were not correlated with the starch accumulating rates and the kernel filling rate, but the SS activity at the middle and late period were highly significantly correlated with the starch accumulating rates and the kernel filling rate. The GBSS activity was highly significantly correlated with the amylose accumulating rate, but not correlated with the kernel filling rate. The SBE activity was highly significantly correlated with the amylopectin accumulating rate and the kernel filling rate. It was not ADPGPPase and DBE, but SS was the rate-limiting factor of starch biosynthesis in developing maize kernels. GBSS had an important effect on amylose accumulation, and SBE had a significant effect on amylopectin accumulation.展开更多
Maize kernel moisture content(KMC)at harvest greatly affects mechanical harvesting,transport and storage.KMC is correlated with kernel dehydration rate(KDR)before and after physiological maturity.KMC and KDR are compl...Maize kernel moisture content(KMC)at harvest greatly affects mechanical harvesting,transport and storage.KMC is correlated with kernel dehydration rate(KDR)before and after physiological maturity.KMC and KDR are complex traits governed by multiple quantitative trait loci(QTL).Their genetic architecture is incompletely understood.We used a multiomics integration approach with an association panel to identify genes influencing KMC and KDR.A genome-wide association study using time-series KMC data from 7 to 70 days after pollination and their transformed KDR data revealed respectively 98and 279 loci significantly associated with KMC and KDR.Time-series transcriptome and proteome datasets were generated to construct KMC correlation networks,from which respectively 3111 and 759 module genes and proteins were identified as highly associated with KMC.Integrating multiomics analysis,several promising candidate genes for KMC and KDR,including Zm00001d047799 and Zm00001d035920,were identified.Further mutant experiments showed that Zm00001d047799,a gene encoding heat shock 70 kDa protein 5,reduced KMC in the late stage of kernel development.Our study provides resources for the identification of candidate genes influencing maize KMC and KDR,shedding light on the genetic architecture of dynamic changes in maize KMC.展开更多
This paper investigates some approximation properties and learning rates of Lipschitz kernel on the sphere. A perfect convergence rate on the shifts of Lipschitz kernel on the sphere, which is faster than O（n-1/2）, ...This paper investigates some approximation properties and learning rates of Lipschitz kernel on the sphere. A perfect convergence rate on the shifts of Lipschitz kernel on the sphere, which is faster than O（n-1/2）, is obtained, where n is the number of parameters needed in the approximation. By means of the approximation, a learning rate of regularized least square algorithm with the Lipschitz kernel on the sphere is also deduced.展开更多
Climate feedbacks have been usually estimated using changes in radiative effects associated with increased global-mean surface temperature. Feedback uncertainties, however, are not only functions of global-mean surfac...Climate feedbacks have been usually estimated using changes in radiative effects associated with increased global-mean surface temperature. Feedback uncertainties, however, are not only functions of global-mean surface temperature increase. In projections by global climate models, it has been demonstrated that the geographical variation of sea surface temperature change brings significant uncertainties into atmospheric circulation and precipitation responses at regional scales. Here we show that the spatial pattern of surface warming is a major contributor to uncertainty in the combined water vapour-lapse rate feedback. This is demonstrated by computing the global-mean radiative effects of changes in air temperature and relative humidity simulated by 31 climate models using a methodology based on radiative kernels. Our results highlight the important contribution of regional climate change to the uncertainty in climate feedbacks, and identify the regions of the world where constraining surface warming patterns would be most effective for higher skill of climate projections.展开更多
文摘In this paper, we define the Weibull kernel and use it to nonparametric estimation of the probability density function (pdf) and the hazard rate function for independent and identically distributed (iid) data. The bias, variance and the optimal bandwidth of the proposed estimator are investigated. Moreover, the asymptotic normality of the proposed estimator is investigated. The performance of the proposed estimator is tested using simulation study and real data.
基金Supported by Natural Science Foundation of Beijing City and National Natural Science Foundation ofChina(2 2 30 4 1 0 0 1 30 1
文摘In this paper, the normal approximation rate and the random weighting approximation rate of error distribution of the kernel estimator of conditional density function f(y|x) are studied. The results may be used to construct the confidence interval of f(y|x) .
文摘In this paper two kernel density estimators are introduced and investigated. In order to reduce bias, we intuitively subtract an estimated bias term from ordinary kernel density estimator. The second proposed density estimator is a geometric extrapolation of the first bias reduced estimator. Theoretical properties such as bias, variance and mean squared error are investigated for both estimators. To observe their finite sample performance, a Monte Carlo simulation study based on small to moderately large samples is presented.
基金grants from the National Natural Science Foundation of China （30471025） Agricultural Science and Technology Span Project （2003, 19） the High Level Person Start-Up Fund of Qingdao Agricultural University, China （630629）.
文摘The filling rate and the starch accumulation in developing maize kernel were analyzed. The changes of enzyme activities associated with sucrose metabolism and starch biosynthesis were investigated. The purpose is to discuss the enzymatic mechanisms responsible for starch synthesis. Two types of maize cultivars （Zea mays）, high starch maize （Feiyu 3） and normal maize （Yuyu 22）, were grown in a corn field. The factors involved in starch synthesis were performed during the growth period. The kernel filling rate, the sucrose content, the starch accumulating rates and the activities of SS （sucrose synthase）, GBSS （granule-bound starch synthase）, SBE （starch branching enzyme） of Feiyu 3, which has high starch content, were significantly higher than those of Yuyu 22, which has low starch content, after 10 DAP （days after pollination）. Correlation analysis indicated that ADPGPPase （ADP-glucose pyrophosphorylase） and DBE （starch debranching enzyme） were not correlated with the starch accumulating rates and the kernel filling rate, but the SS activity at the middle and late period were highly significantly correlated with the starch accumulating rates and the kernel filling rate. The GBSS activity was highly significantly correlated with the amylose accumulating rate, but not correlated with the kernel filling rate. The SBE activity was highly significantly correlated with the amylopectin accumulating rate and the kernel filling rate. It was not ADPGPPase and DBE, but SS was the rate-limiting factor of starch biosynthesis in developing maize kernels. GBSS had an important effect on amylose accumulation, and SBE had a significant effect on amylopectin accumulation.
基金supported by Natural Science Foundation of Shaanxi Province(S2021-JC-WT-006)the National Key Research and Development Program of China(2018YFD0100200)+1 种基金the China Postdoctoral Science Foundation(2018M633588)the China Agriculture Research System(CARS-02-77)。
文摘Maize kernel moisture content(KMC)at harvest greatly affects mechanical harvesting,transport and storage.KMC is correlated with kernel dehydration rate(KDR)before and after physiological maturity.KMC and KDR are complex traits governed by multiple quantitative trait loci(QTL).Their genetic architecture is incompletely understood.We used a multiomics integration approach with an association panel to identify genes influencing KMC and KDR.A genome-wide association study using time-series KMC data from 7 to 70 days after pollination and their transformed KDR data revealed respectively 98and 279 loci significantly associated with KMC and KDR.Time-series transcriptome and proteome datasets were generated to construct KMC correlation networks,from which respectively 3111 and 759 module genes and proteins were identified as highly associated with KMC.Integrating multiomics analysis,several promising candidate genes for KMC and KDR,including Zm00001d047799 and Zm00001d035920,were identified.Further mutant experiments showed that Zm00001d047799,a gene encoding heat shock 70 kDa protein 5,reduced KMC in the late stage of kernel development.Our study provides resources for the identification of candidate genes influencing maize KMC and KDR,shedding light on the genetic architecture of dynamic changes in maize KMC.
文摘众数作为密度函数的最大值点,能有效刻画数据的集中趋势且对异常值具有较强稳健性。然而,在实际应用中,观测数据常因个体失访、退出实验或研究终止等原因出现右删失现象,且数据之间往往具有相依关系。为此,针对宽相依(widely orthant dependent,WOD)这一包含独立、负相依及部分正相依结构的宽泛相依序列,在右删失机制下结合逆概率加权(inverse probability weighting,IPW)方法构造核密度估计量,并据此提出众数的非参数核估计。在紧集和Lipschitz连续等适当条件下,证明密度估计量的一致强相合性,并进一步得出众数估计量的强相合性及其收敛速度。数值模拟和实证分析结果表明,该估计方法在有限样本下表现出良好的估计性能和稳健性,验证其渐近理论性质与实际应用价值。
基金Supported by the National Natural Science Foundation of China(61272023,91330118)
文摘This paper investigates some approximation properties and learning rates of Lipschitz kernel on the sphere. A perfect convergence rate on the shifts of Lipschitz kernel on the sphere, which is faster than O（n-1/2）, is obtained, where n is the number of parameters needed in the approximation. By means of the approximation, a learning rate of regularized least square algorithm with the Lipschitz kernel on the sphere is also deduced.
基金Supported by Nationai Natural Science Foundation of China （61074085）, Beijing Natural Science Foundation （4122029, 4142035）, and the Fundamental Research Funds for the Central Universities （F_RF-SD-12-008B, FRF-AS- 11-004B）
基金The National Natural Science Foundation of China under contract No. 41675070the Shanghai Eastern Scholar Program under contract No. TP2015049+1 种基金the Expert Development Fund under contract No. 2017033the China Scholarship Council under contract No. 201506330007.
文摘Climate feedbacks have been usually estimated using changes in radiative effects associated with increased global-mean surface temperature. Feedback uncertainties, however, are not only functions of global-mean surface temperature increase. In projections by global climate models, it has been demonstrated that the geographical variation of sea surface temperature change brings significant uncertainties into atmospheric circulation and precipitation responses at regional scales. Here we show that the spatial pattern of surface warming is a major contributor to uncertainty in the combined water vapour-lapse rate feedback. This is demonstrated by computing the global-mean radiative effects of changes in air temperature and relative humidity simulated by 31 climate models using a methodology based on radiative kernels. Our results highlight the important contribution of regional climate change to the uncertainty in climate feedbacks, and identify the regions of the world where constraining surface warming patterns would be most effective for higher skill of climate projections.
