A plug-in technique in nonparametric regression with dependence

The problem addressed is that of smoothing parameter selection in kernel nonparametric regression in the fixed design regression model with dependent noise. An asymptotic expression of the optimum bandwidth parameter has been obtained in recent studies, where this takes the form h = C ₀ n ^?1/5. This paper proposes to use a plug-in methodology, in order to obtain an optimum estimation of the bandwidth parameter, through preliminary estimation of the unknown value of C ₀.     

Analyzing Binomial Data in a Split-Plot Design: Classical Approach or Modern Techniques?

Modeling data that are non-normally distributed with random effects is the major challenge in analyzing binomial data in split-plot designs. Seven methods for analyzing such data using mixed, generalized linear, or generalized linear mixed models are compared for the size and power of the tests. This study shows that analyzing random effects properly is more important than adjusting the analysis for non-normality. Methods based on mixed and generalized linear mixed models hold Type I error rates better than generalized linear models. Mixed model methods tend to have higher power than generalized linear mixed models when the sample size is small.     

On constructing sequences estimating the mixing distribution with applications

This paper shows that by minimizing a Chebychev norm a mixing distribution can be constructed which converges weakly to the true mixing distribution with probability one. Deely and Kruse (1968) established a similar result for the supremum norm. For both norms the constructed mixing distribution is computed by solving a linear programming problem, but this problem is considerably smaller when the Chebychev norm is used. Thus a suitable mixing distribution can be constructed from solving a linear programming problem with considerably less computational work than was previously known. To illustrate the application of this simpler procedure it is applied to derive nonparametric empirical Bayes estimates in a simulation study. Some density estimates are also illustrated.     

Income vulnerability of rural households in Bangladesh: a comparison between Bayesian and classical methods

The geographical location and the monsoon climate render Bangladesh highly vulnerable to natural hazards, deteriorating the country's socio-economic stability. This study is based on 500 randomly chosen rural households from the Household Income and Expenditure Survey [Bangladesh Bureau of Statistics, Planning Division, Ministry of Planning, Government of the People's Republic of Bangladesh, Dhaka, 2006]. The objectives are to estimate the income vulnerability of rural households and to check whether the Bayesian approaches (natural conjugate prior and non-informative prior estimates) have any superiority over the classical (feasible generalized least square (FGLS)) method. The poverty level, measured from the data, is 24%; whereas the vulnerability estimates, using FGLS, natural conjugate prior and non-informative prior are 31%, 69% and 82%, respectively. Vulnerability estimates by the Bayesian natural conjugate prior approach is found to have greater efficiency compared with FGLS and non-informative prior approaches.     

数字经济对我国市域农业经济韧性的影响效应与机理分析——基于系统GMM模型与动态门槛模型的检验

基于2011—2019年我国277个市域农业的面板数据,运用反事实方法科学测度了其经济韧性水平,并借助系统GMM模型、中介模型和动态门槛模型等方法,实证检验了数字经济对市域农业经济韧性的影响效应及作用机理。研究发现：数字经济显著增强了市域农业经济韧性,这一结论经一系列稳健性检验后仍能成立;机制分析结果表明,农业资本深化是数字经济提升市域农业经济韧性的重要路径。异质性分析表明,在东部、中部、西部地区和人力资本水平较高的地区,数字经济对市域农业经济韧性的影响效应更为显著,而对东北部地区的提升效应则不显著。动态门槛检验进一步揭示,数字经济对市域农业经济韧性的影响呈现边际递增的非线性特征,当数字经济发展水平越过特定门槛值（0147）时,数字经济对市域农业经济韧性的促进作用显著增强。     

Online Control Charts for Process Averages Based on Repeated Median Filters

Two types of estimates of process level, namely repeated median estimates (Siegel, 1982 Siegel , A. F. ( 1982 ). Robust regression using repeated medians . Biometrika 69 : 242 – 244 .[Crossref], [Web of Science ®] , [Google Scholar]) and full online estimates (Gather et al., 2006 Gather , U. , Schettlinger , K. , Fried , R. ( 2006 ). Online signal extraction by robust linear regression . Computational Statistics 21 : 33 – 51 .[Crossref], [Web of Science ®] , [Google Scholar]) based on repeated median filters, are used to develop control charts. The distributional properties of the estimates are studied using simulation and these are found to closely follow normal distribution. The repeated median being robust against outliers with asymptotically 50% breakdown value and having small standard deviation is found to be useful as a basis for monitoring process averages. The control charts using repeated median estimates have been recommended for general use.