Finite mixture of regression models for a stratified sample

Despite the popularity and importance, there is limited work on modelling data which come from complex survey design using finite mixture models. In this work, we explored the use of finite mixture regression models when the samples were drawn using a complex survey design. In particular, we considered modelling data collected based on stratified sampling design. We developed a new design-based inference where we integrated sampling weights in the complete-data log-likelihood function. The expectation–maximisation algorithm was developed accordingly. A simulation study was conducted to compare the new methodology with the usual finite mixture of a regression model. The comparison was done using bias-variance components of mean square error. Additionally, a simulation study was conducted to assess the ability of the Bayesian information criterion to select the optimal number of components under the proposed modelling approach. The methodology was implemented on real data with good results.     

Generalized estimator of population mean by using conventional and non-conventional measures in the presence of measurement errors

In survey research, it is assumed that reported response by the individual is correct. However, given the issues of prestige bias, self-respect, respondent's reported data often produces estimated values which are highly deviated from the true values. This causes measurement error (ME) to be present in the sample estimates. In this article, the estimation of population mean in the presence of measurement error using information on a single auxiliary variable is studied. A generalized estimator of population mean is proposed. The class of estimators is obtained by using some conventional and non-conventional measures. Simulation and numerical study is also conducted to assess the performance of estimators in the presence and absence of measurement error.     

A new aging concept derived from the increasing convex ordering

In this paper, a comparison between the life distribution of a new unit with that of a used unit in the increasing convex order is made leading to a new class of life distributions which we call “new better than used in convex ordering of second order”. This class includes as subclasses the NBU and the NBUC and is a subclass of the NBUCA class. Preservation properties under convolution, random maxima, mixing and formation of coherent structures are established. Stochastic comparisons of the excess lifetime when the inter-arrival times belong to the NBUC(2) class are developed. Some applications of Poisson shock models and a test of exponentiality against NBUC(2) alternative are presented.     

Inferences for a Partially Varying Coefficient Model With Endogenous Regressors

In this article, we propose a new class of semiparametric instrumental variable models with partially varying coefficients, in which the structural function has a partially linear form and the impact of endogenous structural variables can vary over different levels of some exogenous variables. We propose a three-step estimation procedure to estimate both functional and constant coefficients. The consistency and asymptotic normality of these proposed estimators are established. Moreover, a generalized F-test is developed to test whether the functional coefficients are of particular parametric forms with some underlying economic intuitions, and furthermore, the limiting distribution of the proposed generalized F-test statistic under the null hypothesis is established. Finally, we illustrate the finite sample performance of our approach with simulations and two real data examples in economics.     

Efficient Bayesian inference in generalized inverse gamma processes for stochastic volatility

This paper develops a novel and efficient algorithm for Bayesian inference in inverse Gamma stochastic volatility models. It is shown that by conditioning on auxiliary variables, it is possible to sample all the volatilities jointly directly from their posterior conditional density, using simple and easy to draw from distributions. Furthermore, this paper develops a generalized inverse gamma process with more flexible tails in the distribution of volatilities, which still allows for simple and efficient calculations. Using several macroeconomic and financial datasets, it is shown that the inverse gamma and generalized inverse gamma processes can greatly outperform the commonly used log normal volatility processes with Student’s t errors or jumps in the mean equation.     

On approximations via convolution-defined mixture models

An often-cited fact regarding mixing or mixture distributions is that their density functions are able to approximate the density function of any unknown distribution to arbitrary degrees of accuracy, provided that the mixing or mixture distribution is sufficiently complex. This fact is often not made concrete. We investigate and review theorems that provide approximation bounds for mixing distributions. Connections between the approximation bounds of mixing distributions and estimation bounds for the maximum likelihood estimator of finite mixtures of location-scale distributions are reviewed.     

Cytometry inference through adaptive atomic deconvolution

In this paper, we consider a statistical estimation problem known as atomic deconvolution. Introduced in reliability, this model has a direct application when considering biological data produced by flow cytometers. From a statistical point of view, we aim at inferring the percentage of cells expressing the selected molecule and the probability distribution function associated with its fluorescence emission. We propose here an adaptive estimation procedure based on a previous deconvolution procedure introduced by Es, Gugushvili, and Spreij [(2008), ‘Deconvolution for an atomic distribution’, Electronic Journal of Statistics, 2, 265–297] and Gugushvili, Es, and Spreij [(2011), ‘Deconvolution for an atomic distribution: rates of convergence’, Journal of Nonparametric Statistics, 23, 1003–1029]. For both estimating the mixing parameter and the mixing density automatically, we use the Lepskii method based on the optimal choice of a bandwidth using a bias-variance decomposition. We then derive some convergence rates that are shown to be minimax optimal (up to some log terms) in Sobolev classes. Finally, we apply our algorithm on the simulated and real biological data.     

国家创新体系视角下的国家创新能力测度述评——理论方法、数据基础及中国实践

文章从国家创新体系角度,对创新能力测度相关的理论基础、方法工具、科技统计调查及中国的研究与实践进行全面梳理和分析。国家创新能力测度的发展与实践表明:国家创新体系理论(NIS理论)以系统论为指导全面考察创新活动的发生机制,为准确测度国家创新能力提供了有力支撑;不同时期形成的创新能力测度方法与当时占主流地位的创新理论密切相关;当前占主导地位的测度方法可分为建模计量法、综合指标法和DEA效率评价法三类,都是以NIS理论为支撑的;规范的科技统计调查是准确测度创新能力的前提,OECD是这方面的典范,其经验为发展中国家提供了参考依据;中国学者在测度方法的探索上有诸多独到之处,但国内科技统计调查工作仍有待进一步规范。     

Quality_Family Deployment: A New Perspective in Determining Priority Importance for Improving Work Performance in Organization

Determining priority importance is a matter of concerns among the organization to improve their performance. One of the important aspects that should be considered by the organization is management of human resources, comprising of members who have their own family life. In this paper, we deliver a new perspective for organization to provide priority importance for their members with respect to family matters in order to inculcate the sense of belonging in the organization. To be effective in considering family matters in the organizational policy making, closer look of family characteristics are required. The idea of translating several family characteristics as quality variables and applying the quality function deployment (QFD) method to these variables could present a new way of improving the decision making in the organization by considering the process of decision in the family. Quality function deployment for family (QFDF) produces a friendly interpretation of a highly complex and intangible matters around family life; thus, making the assessment of a family easier. QFD is applied on the data gathered from a questionnaire survey based on 1,213 families in West Malaysia, Malaysia. Twelve variables are identified as voice of family, where seven of them are found to have the highest priority of importance. These variables could also be translated into quality variables in the context of organization, the strategy of improvement for the family could be interpreted as strategy for improvement in the organization. Furthermore, the results of this study provide suggestion to improve actions for managing human resource. In the discussion, three most high ranked variables from both perspectives of family and organization are considered.     

中国生育率研究方法:30年回眸

改革开放30年是我国人口学及人口研究迅速成长的30年。生育率研究方法从一个侧面反映出改革开放以来我国人口学研究方法的发展。中国的生育率研究方法既有从西方引进的各种生育率指标和模型,也有中国学者为了适应自己的需要而改进和创建的方法和模型。笔者从生育率度量指标和生育率模型两个方面总结我国生育率研究方法的应用及变化。对在中国生育率研究中所使用的主要方法进行回顾并对这些方法对我国生育率研究的贡献进行总结。