权数对CPI的结果影响程度定量分析

权数是影响CPI精度的重要因素之一,通过对基本分类价格指数计算中的权数缺失和高层级价格指数计算中权数滞后的影响进行了理论和实证分析,结果表明,利用将销售量作为权数的联合比法对基本分类价格指数进行计算可以大幅提高其精度;高层级价格指数计算所用权数的滞后性同样会降低CPI的精度,且主要存在高估CPI的系统性误差问题。     

Pareto analysis for the lifetime performance index of products on the basis of progressively first-failure-censored batches under balanced symmetric and asymmetric loss functions

One of the most important topics in manufacturing industries is the evaluation of performance lifetimes of products. Based on a given lifetime performance index, this paper deals with evaluating the performance of a process subject to a given lower specification limit. We confine ourselves to the progressively first-failure-censored data coming from a common Pareto distribution. With both the Bayesian and the non-Bayesian approaches being investigated here, we pay more attention to Bayesian estimators under balanced type loss functions. The results are presented under the balanced versions of two well-known loss functions, namely the squared error loss and the Varian's linear-exponential (LINEX) loss. Moreover, based on the Bayesian and the non-Bayesian approaches, the problem of testing hypotheses on the lifetime performance index is studied. Also, a simulation study is performed to assess the obtained results. Finally, two illustrative examples are given.     

A J‐function for Inhomogeneous Spatio‐temporal Point Processes

We propose a new summary statistic for inhomogeneous intensity‐reweighted moment stationarity spatio‐temporal point processes. The statistic is defined in terms of the n‐point correlation functions of the point process, and it generalizes the J‐function when stationarity is assumed. We show that our statistic can be represented in terms of the generating functional and that it is related to the spatio‐temporal K‐function. We further discuss its explicit form under some specific model assumptions and derive ratio‐unbiased estimators. We finally illustrate the use of our statistic in practice. © 2014 Board of the Foundation of the Scandinavian Journal of Statistics     

Statistical Inference for Single‐index Panel Data Models

We study estimation and hypothesis testing in single‐index panel data models with individual effects. Through regressing the individual effects on the covariates linearly, we convert the estimation problem in single‐index panel data models to that in partially linear single‐index models. The conversion is valid regardless of the individual effects being random or fixed. We propose an estimating equation approach, which has a desirable double robustness property. We show that our method is applicable in single‐index panel data models with heterogeneous link functions. We further design a chi‐squared test to evaluate whether the individual effects are random or fixed. We conduct simulations to demonstrate the finite sample performance of the method and conduct a data analysis to illustrate its usefulness.     

Estimation and Comparison of Signed Symmetric Covariation Coefficient and Generalized Association Parameter for Alpha-stable Dependence Modeling

In this paper, we study the estimators of two measures of dependence: the signed symmetric covariation coefficient (scov) proposed by Garel and Kodia and the generalized association parameter (g.a.p.) put forward by Paulauskas. In the sub-Gaussian case, the scov and the g.a.p. coincide. The estimator of the scov proposed here is based on fractional lower-order moments. The estimator of the g.a.p. is based on estimation of a stable spectral measure. We investigate the relative performance of these estimators by comparing results from simulations.     

A table of some percentage points of the distribution of a difference between independent chi-square variables

The distribution of Bell-Doksum measure of correlation is that of a difference between independent chi-square variables with equal weights. A table of percentage points computed here for the distribution may be used to test a hypothesis of no correlation between two variables. The distribution of a diffference between independent chi-square variables is also useful in studying variance component estimators and some general results corresponding to the distribution are given.     

Skewed zero-bound distributions and process capability indices for upper specifications

A common practical situation in process capability analysis, which is not well developed theoretically, is when the quality characteristic of interest has a skewed distribution with a long tail towards relatively large values and an upper specification limit only exists. In such situations, it is not uncommon that the smallest possible value of the characteristic is 0 and this is also the best value to obtain. Hence a target value 0 is assumed to exist. We investigate a new class of process capability indices for this situation. Two estimators of the proposed index are studied and the asymptotic distributions of these estimators are derived. Furthermore, we suggest a decision procedure useful when drawing conclusions about the capability at a given significance level, based on the estimated indices and their asymptotic distributions. A simulation study is also performed, assuming that the quality characteristic is Weibull-distributed, to investigate the true significance level when the sample size is finite.     

Comparison of the several parameterized estimators for the positive extreme value index

In the paper we compare several parameterized estimators for the positive extreme value index, which is a very important parameter appearing in the estimation of the probability of rare events. Firstly, asymptotic comparison at optimal levels of the corresponding tail index estimators is performed. Secondly, the practical validation of asymptotic results for moderate finite samples is done by means of Monte-Carlo simulations. We demonstrate that theoretical domination of the positive extreme value index estimators, which are asymptotically normal with a null asymptotic bias, is not reflected in Monte-Carlo simulations. Moreover, the estimators of such type do not demonstrate stability in the sense of empirical mean-squared error.     

Designing of a mixed-chain sampling plan based on the process capability index with chain sampling as the attributes plan

In this article, we propose a new mixed chain sampling plan based on the process capability index C_pk, where the quality characteristic of interest having double specification limits and follows the normal distribution with unknown mean and variance. In the proposed mixed plan, the chain sampling inspection plan is used for the inspection of attribute quality characteristics. The advantages of this proposed mixed sampling plan are also discussed. Tables are constructed to determine the optimal parameters for practical applications by formulating the problem as a non linear programming in which the objective function to be minimized is the average sample number and the constraints are related to lot acceptance probabilities at acceptable quality level and limiting quality level under the operating characteristic curve. The practical application of the proposed mixed sampling plan is explained with an illustrative example. Comparison of the proposed sampling plan is also made with other existing sampling plans.     

Some Sampling Properties of a Model for Income Distribution

A recently proposed model for describing the distribution of income over a population, based on the Burr distribution, has been shown to fit better than the commonly used lognormal or gamma distributions. The current article extends that analysis by deriving the large-sample properties of the maximum likelihood estimates for this three-parameter model. Consequently, resulting confidence intervals for some measures of income inequality (including the Gini index) are used to further test the model's validity, as well as to examine apparent trends in inequality over time. Since these properties depend on the way the income data are grouped and censored, implications for choosing data-report intervals can be analyzed. Specifically, a choice between two common methods of reporting the data is shown to have an important impact on Gini index estimates.