共查询到20条相似文献,搜索用时 31 毫秒
1.
《Econometric Reviews》2013,32(3):383-393
ABSTRACT This paper considers computation of fitted values and marginal effects in the Box–Cox regression model. Two methods, 1 the “smearing” technique suggested by Duan (see Ref. [10]) and 2 direct numerical integration, are examined and compared with the “naive” method often used in econometrics. 相似文献
2.
《统计学通讯:理论与方法》2013,42(4):785-786
ABSTRACT The concept of generalized order statistics was introduced by Kamps (1995) to unify several concepts that have been used in statistics such as order statistics, record values, and sequential order statistics. Estimation of the parameters of the Burr type XII distribution are obtained based on generalized order statistics. The maximum likelihood and Bayes methods of estimation are used for this purposes. The Bayes estimates are derived by using the approximation form of Lindley (1980). Estimation based on upper records from the Burr model is obtained and compared by using Monte Carlo simulation study. Our results are specialized to the results of AL-Hussaini and Jaheen (1992) which are based on ordinary order statistics. 相似文献
3.
《统计学通讯:理论与方法》2013,42(9):1515-1529
ABSTRACT This paper develops corrected score tests for heteroskedastic t regression models, thus generalizing results by Cordeiro, Ferrari and Paula[1] and Cribari-Neto and Ferrari[2] for normal regression models and by Ferrari and Arellano-Valle[3] for homoskedastic t regression models. We present, in matrix notation, Bartlett-type correction formulae to improve score tests in this class of models. The corrected score statistics have a chi-squared distribution to order n ?1, where n is the sample size. We apply our main result to a few special models and present simulation results comparing the performance of the usual score tests and their corrected versions. 相似文献
4.
I. Ardoino E. M. Biganzoli C. Bajdik P. J. Lisboa P. Boracchi F. Ambrogi 《Journal of applied statistics》2012,39(7):1409-1421
In cancer research, study of the hazard function provides useful insights into disease dynamics, as it describes the way in which the (conditional) probability of death changes with time. The widely utilized Cox proportional hazard model uses a stepwise nonparametric estimator for the baseline hazard function, and therefore has a limited utility. The use of parametric models and/or other approaches that enables direct estimation of the hazard function is often invoked. A recent work by Cox et al. [6] has stimulated the use of the flexible parametric model based on the Generalized Gamma (GG) distribution, supported by the development of optimization software. The GG distribution allows estimation of different hazard shapes in a single framework. We use the GG model to investigate the shape of the hazard function in early breast cancer patients. The flexible approach based on a piecewise exponential model and the nonparametric additive hazards model are also considered. 相似文献
5.
This article suggests random and fixed effects spatial two-stage least squares estimators for the generalized mixed regressive spatial autoregressive panel data model. This extends the generalized spatial panel model of Baltagi et al. (2013) by the inclusion of a spatial lag term. The estimation method utilizes the Generalized Moments method suggested by Kapoor et al. (2007) for a spatial autoregressive panel data model. We derive the asymptotic distributions of these estimators and suggest a Hausman test a la Mutl and Pfaffermayr (2011) based on the difference between these estimators. Monte Carlo experiments are performed to investigate the performance of these estimators as well as the corresponding Hausman test. 相似文献
6.
Thomas Parker 《统计学通讯:理论与方法》2017,46(11):5195-5202
In this note, it is shown that the finite-sample distributions of the Wald, likelihood ratio, and Lagrange multiplier statistics in the classical linear regression model are members of the generalized beta model introduced by McDonald and Xu (1995a). This is useful for examining the properties of these test statistics. For example, this characterization makes it easy to find distribution, quantile, and density functions for each test statistic, makes it clear why Wald tests may overreject the null hypothesis using asymptotic critical values, and formalizes the fact that the Lagrange multiplier statistic follows a distribution with bounded support. 相似文献
7.
Gauss M. Cordeiro Maria Do Carmo S. Lima Audrey H.M.A. Cysneiros Marcelino A. R. Pascoa Rodrigo R. Pescim 《统计学通讯:理论与方法》2013,42(8):2268-2297
AbstractBirnbaum and Saunders (1969a) pioneered a lifetime model which is commonly used in reliability studies. Based on this distribution, a new model called the gamma Birnbaum–Saunders distribution is proposed for describing fatigue life data. Several properties of the new distribution including explicit expressions for the ordinary and incomplete moments, generating and quantile functions, mean deviations, density function of the order statistics, and their moments are derived. We discuss the method of maximum likelihood and a Bayesian approach to estimate the model parameters. The superiority of the new model is illustrated by means of three failure real data sets. We also propose a new extended regression model based on the logarithm of the new distribution. The last model can be very useful to the analysis of real data and provide more realistic fits than other special regression models. 相似文献
8.
Several generalizations to the concept of Kullback-Leibler divergence measure and Kerridge inaccuracy measure are available in the literature. In a recent paper Kundu (Metrika, 78:415–435, 2015) considered a generalized K-L divergence measure of order (α, β). Nath (Metrika, 13:123–135, 1968) has also proposed generalized inaccuracy measure of order α. Here we address the question of extending these measures to higher dimensions with reference to residual lifetimes. In the present work, the generalized divergence and inaccuracy measures are extended for conditional lifetimes of two components having possibly different ages. Several properties, including monotonicity, and bounds of these measures are obtained for conditional random variables. Moreover, we study the effect of (increasing) monotone transformation on these generalized measures. 相似文献
9.
In this article, we consider the unbalanced case of the three fold nested random effects model under partial balance. The distributions of unweighted sums of squares are obtained first. Using the method of generalized p value introduced in Tsui and Weerahandi (1989), a new method is proposed for hypothesis tests involving functions of variance components. To evaluate the sizes of the generalized p value, a simulation study is conducted. The results indicate that the proposed method performs well under all examined conditions. 相似文献
10.
We derive explicit expressions for the moments, incomplete moments, quantile function and generating function of the additive Weibull model pioneered by Xie and Lai (1995), which is a quite flexible distribution for fitting lifetime data with bathtub-shaped failure rate function. In addition, we estimate the model parameters by maximum likelihood and determine the observed information matrix. The flexibility of the additive Weibull distribution is illustrated by means of one application to real data. 相似文献
11.
Pao-Sheng Shen 《统计学通讯:理论与方法》2013,42(1):128-137
Consider the model φ(S(y | X)) = β(y) T X, where φ is a known link function, S(· | X) is the survival function of a response Y given a covariate X = (1, X, X 2,…, X p ), and β(y) is an unknown vector of time-dependent regression coefficients. The response Y is subject to left truncation and right censoring. We assume that given X, Y is independent of (C, T) where C and T are censoring and truncation variables with P(C ≥ T) = 1. In this article, with some modification of the assumptions in Lemmas 5 and 6 of Iglesias-Pérez and González-Manteiga (1999), we present an almost sure representation for the generalized product-limit estimator (GPL) of S(y | X). Based on the GPL and the approach of Teodorescu et al. (2010), a least squares estimator of β(y) is obtained and a bootstrap procedure is proposed to choose the optimum bandwidth. 相似文献
12.
《统计学通讯:理论与方法》2013,42(10):2043-2052
Abstract Chiu [Chiu, S. N. (1999). An unbiased estimator for the survival function of censored data. Commun. Statist. - Theory Meth. 28(9):2249–2260.] proposed a nonparametric estimator for the survival function which is based on observable censoring times in the general censoring model. His estimator is less efficient than the Product-Limit estimator. Considering an informative censoring model this drawback can partially be overcome. This is shown by a nonparametric, uniformly consistent estimator based on observable censoring times within the simple Koziol–Green model. Some asymptotic properties of the new estimator are investigated and it is compared with the well-known ACL-estimator. 相似文献
13.
Xinmin Li 《统计学通讯:理论与方法》2013,42(2):204-212
In the article, we consider the unbalanced case of the two-way nested random effects model under partial balance. Using the method of generalized confidence intervals (GCIs) introduced in Weeranhandi (1993 1995), a new method is proposed for constructing confidence intervals on linear function of variance components. To compare the resulted intervals with the Modified Large Sample (MLS) intervals by Hernandez and Burdick (1993), a simulation study is conducted. The results indicate that the proposed method performs better than the MLS method, especially for very unbalanced designs. 相似文献
14.
Changyong Feng Hongyue Wang Yun Zhang Yu Han Yuefeng Liang Xin M. Tu 《统计学通讯:理论与方法》2017,46(7):3489-3500
Andersen's plot, a graphical method for testing the proportionality assumption in the Cox Regression Model (Cox, 1972), first proposed by Kay (1977) and popularized by Andersen (1982), has been used widely in biomedical research to check the validity of applying this popular regression model in survival analysis. Our theoretical derivation and examples show that the theoretical basis of this method is flawed. The graphical method should not be used in testing the proportionality. Instead, formal analytical methods based on residuals such as Cox–Snell residual and martingale residual should be used in practice. 相似文献
15.
Fernanda B. Rizzato Roseli A. Leandro Clarice G.B. Demétrio 《Journal of applied statistics》2016,43(11):2085-2109
In this paper, we consider a model for repeated count data, with within-subject correlation and/or overdispersion. It extends both the generalized linear mixed model and the negative-binomial model. This model, proposed in a likelihood context [17,18] is placed in a Bayesian inferential framework. An important contribution takes the form of Bayesian model assessment based on pivotal quantities, rather than the often less adequate DIC. By means of a real biological data set, we also discuss some Bayesian model selection aspects, using a pivotal quantity proposed by Johnson [12]. 相似文献
16.
R. Hasan Abadi 《统计学通讯:模拟与计算》2013,42(8):1430-1443
Censored data arise naturally in a number of fields, particularly in problems of reliability and survival analysis. There are several types of censoring, in this article, we will confine ourselves to the right randomly censoring type. Recently, Ahmadi et al. (2010) considered the problem of estimating unknown parameters in a general framework based on the right randomly censored data. They assumed that the survival function of the censoring time is free of the unknown parameter. This assumption is sometimes inappropriate. In such cases, a proportional odds (PO) model may be more appropriate (Lam and Leung, 2001). Under this model, in this article, point and interval estimations for the unknown parameters are obtained. Since it is important to check the adequacy of models upon which inferences are based (Lawless, 2003, p. 465), two new goodness-of-fit tests for PO model based on right randomly censored data are proposed. The proposed procedures are applied to two real data sets due to Smith (2002). A Monte Carlo simulation study is conducted to carry out the behavior of the estimators obtained. 相似文献
17.
Trias Wahyuni Rakhmawati Geert Molenberghs Geert Verbeke Christel Faes 《Journal of applied statistics》2017,44(4):620-641
Since the seminal paper by Cook and Weisberg [9], local influence, next to case deletion, has gained popularity as a tool to detect influential subjects and measurements for a variety of statistical models. For the linear mixed model the approach leads to easily interpretable and computationally convenient expressions, not only highlighting influential subjects, but also which aspect of their profile leads to undue influence on the model's fit [17]. Ouwens et al. [24] applied the method to the Poisson-normal generalized linear mixed model (GLMM). Given the model's nonlinear structure, these authors did not derive interpretable components but rather focused on a graphical depiction of influence. In this paper, we consider GLMMs for binary, count, and time-to-event data, with the additional feature of accommodating overdispersion whenever necessary. For each situation, three approaches are considered, based on: (1) purely numerical derivations; (2) using a closed-form expression of the marginal likelihood function; and (3) using an integral representation of this likelihood. Unlike when case deletion is used, this leads to interpretable components, allowing not only to identify influential subjects, but also to study the cause thereof. The methodology is illustrated in case studies that range over the three data types mentioned. 相似文献
18.
In some survival studies, the exact time of the event of interest is unknown, but the event is known to have occurred during a particular period of time (interval-censored data). If the diagnostic tool used to detect the event of interest is not perfectly sensitive and specific, outcomes may be mismeasured; a healthy subject may be diagnosed as sick and a sick one may be diagnosed as healthy. In such cases, traditional survival analysis methods produce biased estimates for the time-to-failure distribution parameters (Paggiaro and Torelli 2004). In this context, we developed a parametric model that incorporates sensitivity and specificity into a grouped survival data analysis (a case of interval-censored data in which all subjects are tested at the same predetermined time points). Inferential aspects and properties of the methodology, such as the likelihood function and identifiability, are discussed in this article. Assuming known and non differential misclassification, Monte Carlo simulations showed that the proposed model performed well in the case of mismeasured outcomes; the estimates of the relative bias of the model were lower than those provided by the naive method that assumes perfect sensitivity and specificity. The proposed methodology is illustrated by a study related to mango tree lifetimes. 相似文献
19.
We consider the problem of estimating the lifetime distributions of survival times subject to a general censoring scheme called “middle censoring”. The lifetimes are assumed to follow a parametric family of distributions, such as the Gamma or Weibull distributions, and is applied to cases when the lifetimes come with covariates affecting them. For any individual in the sample, there is an independent, random, censoring interval. We will observe the actual lifetime if the lifetime falls outside of this censoring interval, otherwise we only observe the interval of censoring. This censoring mechanism, which includes both right- and left-censoring, has been called “middle censoring” (see Jammalamadaka and Mangalam, 2003). Maximum-likelihood estimation of the parameters as well as their large-sample properties are studied under this censoring scheme, including the case when covariates are available. We conclude with an application to a dataset from Environmental Economics dealing with ContingentValuation of natural resources. 相似文献
20.
Pao-Sheng Shen 《统计学通讯:理论与方法》2013,42(18):3796-3811
In this article, we consider fitting a semiparametric linear model to survey data with censored observations. The specific goal of the paper is to extend the methods of Cheng et al. (1995) and Chen et al. (2002) to the case when the sample has been drawn from a population using a complex sampling design. Similar to the approach of Lin (2000), we regard the survey population as a random sample from an infinite universe and accounts for this randomness in the statistical inference. A simulation study is conducted to investigate the performance of the proposed estimators. 相似文献