Tests for Equality of Parameters of Two Exponential Distributions with Common Known Coefficient of Variation

ABSTRACT

This article considers the problem of testing equality of parameters of two exponential distributions having common known coefficient of variation, both under unconditional and conditional setup. Unconditional tests based on BLUE'S and LRT are considered. Using the Conditionality Principle of Fisher, an UMP conditional test for one-sided alternative is derived by conditioning on an ancillary. This test is seen to be uniformly more powerful than unconditional tests in certain given ranges of ancillary. Simulation studies on the power functions of the tests are done for this purpose.     

《庄子》一价形容词简单谓语句的句型及其结构模式

《庄子》一价形容词简单谓语句的基本句型共有四种：（1）s＋PAnl（共310句）（2）S＋Adv＋PAnl（共227句）（3）S＋PAnl＋C（26句）（4）s＋PAnl＋O（2句）。句型（1）有6种不同的结构模式，句型（2）作状语的主要是副词、带词尾的状态形容词、介宾短语等，句型（3）中作补语的主要是介宾短语，句型（4）宾语是形容词的配价补足语。     

A diagnostic statistic for functional-coefficient autoregressive models

In this paper, functional coefficient autoregressive (FAR) models proposed by Chen and Tsay (1993) are considered. We propose a diagnostic statistic for FAR models constructed by comparing between parametric and nonparametric estimators of the functional form of the FAR models. We show asymptotic properties of our statistic mathematically and it can be applied to the estimation of the delay parameter and the specification of the functional form of FAR models.     

A Qualitative Evaluation of a Conditional Cash Transfer Program in Turkey: The Beneficiaries’ and Key Informants’ Perspectives

ABSTRACT

Since the 2001 economic crisis, conditional cash transfers (CCTs) have been provided to poor families in Turkey to improve education and health outcomes of children. Under the framework of CCT programs, grants provide an incentive for poor households to use available basic social services. The aim of this study is to explore beneficiaries’ perspectives in relation to a CCT program in Turkey. The in-depth study design entailed semistructured qualitative interviews with beneficiary households and key informants. A total of 397 in-depth interviews were conducted. Analysis results suggest that the CCT program not only positively affected health and educational outcomes, but also contributed to the empowerment of women and improved the self-esteem and self-confidence of beneficiary children. Recommendations for future research are made including the need for an impact evaluation analysis that employs quantitative research methods designed to improve the provision and quality of the basic social services.     

Identifiable finite mixtures of location models for clustering mixed-mode data

For clustering mixed categorical and continuous data, Lawrence and Krzanowski (1996) proposed a finite mixture model in which component densities conform to the location model. In the graphical models literature the location model is known as the homogeneous Conditional Gaussian model. In this paper it is shown that their model is not identifiable without imposing additional restrictions. Specifically, for g groups and m locations, (g!)m–1 distinct sets of parameter values (not including permutations of the group mixing parameters) produce the same likelihood function. Excessive shrinkage of parameter estimates in a simulation experiment reported by Lawrence and Krzanowski (1996) is shown to be an artifact of the model's non-identifiability. Identifiable finite mixture models can be obtained by imposing restrictions on the conditional means of the continuous variables. These new identified models are assessed in simulation experiments. The conditional mean structure of the continuous variables in the restricted location mixture models is similar to that in the underlying variable mixture models proposed by Everitt (1988), but the restricted location mixture models are more computationally tractable.     

MULTIPLE-RECORD SYSTEMS ESTIMATION USING LATENT CLASS MODELS

Capture–recapture methods (also referred to as 'multiple-record systems') have been widely used in enumerating human populations in the fields of epidemiology and public health. In this article, we introduce latent class models into multiple-record systems to account for unobserved heterogeneity in the population. Two approaches, the full and the conditional likelihood, are proposed to estimate the unknown population abundance. We also suggest rules to diagnose identifiability of the proposed latent class models. The methodologies are illustrated by two real examples: the first is to count the undercount of homelessness in the Adelaide central business district, and the second concerns the incidence of diabetes in a small Italian town.     

Splines for financial volatility

Summary.  We propose a flexible generalized auto-regressive conditional heteroscedasticity type of model for the prediction of volatility in financial time series. The approach relies on the idea of using multivariate B -splines of lagged observations and volatilities. Estimation of such a B -spline basis expansion is constructed within the likelihood framework for non-Gaussian observations. As the dimension of the B -spline basis is large, i.e. many parameters, we use regularized and sparse model fitting with a boosting algorithm. Our method is computationally attractive and feasible for large dimensions. We demonstrate its strong predictive potential for financial volatility on simulated and real data, and also in comparison with other approaches, and we present some supporting asymptotic arguments.     

附条件逮捕之理论初探

附条件逮捕发端于司法实践,对协调办案需要和人权保障意义重大。但各地运行状况并不统一,学界也存在着一定的理论争议。对此可以从文本认同、理论认同和感情认同三个角度加以探讨,既指出理论质疑,也阐明其存在的合理性和改善的必要性。     

Measurement Error Correction by Exploiting Gene–Environment Independence in Family‐Based Case–Control Studies

Abstract. Family‐based case–control designs are commonly used in epidemiological studies for evaluating the role of genetic susceptibility and environmental exposure to risk factors in the etiology of rare diseases. Within this framework, it is often reasonable to assume genetic susceptibility and environmental exposure being conditionally independent of each other within families in the source population. We focus on this setting to explore the situation of measurement error affecting the assessment of the environmental exposure. We correct for measurement error through a likelihood‐based method. We exploit a conditional likelihood approach to relate the probability of disease to the genetic and the environmental risk factors. We show that this approach provides less biased and more efficient results than that based on logistic regression. Regression calibration, instead, provides severely biased estimators of the parameters. The comparison of the correction methods is performed through simulation, under common measurement error structures.     

C14. Moments of the kolmogorov-smirnov one-sample statistic

In adaptive estimation, it is often considered that an estimator has made a mistake if the component estimator chosen for use is not the most efficient for the distribution sampled. Theoretical and simulation results point to a fallacy in this line of thought. The Monte Carlo study involves extension of the Princeton Swindle to distributions conditional on a location and scale-free statistic, and to the uniform. The results give a partial explanation for the sometimes surprising robustness of adaptive L-estimators.