• Metrika (IF 0.679) Pub Date : 2020-07-10
Dankmar Böhning, Helen E. Ogden

The paper discusses very general extensions to existing inflation models for discrete random variables, allowing an arbitrary set of points in the sample space to be either inflated or deflated relative to a baseline distribution. The term flation is introduced to cover either inflation or deflation of counts. Examples include one-inflated count models where the baseline distribution is zero-truncated

更新日期：2020-07-10
• Metrika (IF 0.679) Pub Date : 2020-07-09
Liuqing Yang, Yongdao Zhou, Min-Qian Liu

Computer experiments play a crucial role when physical experiments are expensive or difficult to be carried out. As a kind of designs for computer experiments, maximin distance designs have been widely studied. Many existing methods for obtaining maximin distance designs are based on stochastic algorithms, and these methods will be infeasible when the run size or number of factors is large. In this

更新日期：2020-07-10
• Metrika (IF 0.679) Pub Date : 2020-07-09
Michael Stephanou, Melvin Varughese

Hermite series based distribution function estimators have recently been applied in the context of sequential quantile estimation. These distribution function estimators are particularly useful because they allow the online (sequential) estimation of the full cumulative distribution function. This is in contrast to the empirical distribution function estimator and smooth kernel distribution function

更新日期：2020-07-09
• Metrika (IF 0.679) Pub Date : 2020-07-08
Benjamin Auder, Elisabeth Gassiat, Mor Absa Loum

We consider finite mixtures of generalized linear models with binary output. We prove that cross moments (between the output and the regression variables) up to order three are sufficient to identify all parameters of the model. We propose a least-squares estimation method based on those moments and we prove the consistency and the Gaussian asymptotic behavior of the estimator. We provide simulation

更新日期：2020-07-09
• Metrika (IF 0.679) Pub Date : 2020-07-06
Junichi Hirukawa, Sangyeol Lee

In this study, we derive the limiting distribution of the least squares estimator (LSE) and the localized LSE for mildly explosive autoregressive models with locally stationary disturbance and verify that it is Cauchy as in the iid case. We also investigate the limiting distribution of two types of Dickey–Fuller unit root tests, designed for detecting a bubble period in economic time series data, and

更新日期：2020-07-07
• Metrika (IF 0.679) Pub Date : 2020-06-25
Guangbao Guo, Guoqi Qian, Lu Lin, Wei Shao

In recent years, big datasets are often split into several subsets due to the storage requirements. We propose a parallel group Bayesian method for statistical inference in sparse big data. This method improves the existing methods in two aspects: the total datasets are also split into a data subset sequence and the parameter vector is divided into several sub-vectors. Besides, we add a weight sequence

更新日期：2020-06-26
• Metrika (IF 0.679) Pub Date : 2020-06-24
Marko Voutilainen, Pauliina Ilmonen, Soledad Torres, Ciprian Tudor, Lauri Viitasaari

The classical ARCH model together with its extensions have been widely applied in the modeling of financial time series. We study a variant of the ARCH model that takes account of liquidity given by a positive stationary process. We provide minimal assumptions that ensure the existence and uniqueness of the stationary solution for this model. Moreover, we give necessary and sufficient conditions for

更新日期：2020-06-25
• Metrika (IF 0.679) Pub Date : 2020-06-23
Anne Philippe, Caroline Robet, Marie-Claude Viano

This paper investigates second order properties of a stationary continuous time process after random sampling. While a short memory process always gives rise to a short memory one, we prove that long-memory can disappear when the sampling law has very heavy tails. Despite the fact that the normality of the process is not maintained by random sampling, the normalized partial sum process converges to

更新日期：2020-06-23
• Metrika (IF 0.679) Pub Date : 2020-06-19
Zongliang Hu, Zhishui Hu, Kai Dong, Tiejun Tong, Yuedong Wang

In this paper, we propose a shrinkage framework for jointly estimating multiple covariance matrices by shrinking the sample covariance matrices towards the pooled sample covariance matrix. This framework allows us to borrow information across different groups. We derive the optimal shrinkage parameters under the Stein and quadratic loss functions, and prove that our derived estimators are asymptotically

更新日期：2020-06-19
• Metrika (IF 0.679) Pub Date : 2020-06-09
Xiong Cai, Liugen Xue, Xiaolong Pu, Xingyu Yan

In this article, we focus on the estimation of varying-coefficient mixed effects models for longitudinal and sparse functional response data, by using the generalized least squares method coupling a modified local kernel smoothing technique. This approach provides a useful framework that simultaneously takes into account the within-subject covariance and all observation information in the estimation

更新日期：2020-06-09
• Metrika (IF 0.679) Pub Date : 2020-06-06
Suman Majumder, Adhidev Biswas, Tania Roy, Subir Kumar Bhandari, Ayanendranath Basu

We discuss a new weighted likelihood method for robust parametric estimation. The method is motivated by the need for generating a simple estimation strategy which provides a robust solution that is simultaneously fully efficient when the model is correctly specified. This is achieved by appropriately weighting the score function at each observation in the maximum likelihood score equation. The weight

更新日期：2020-06-06
• Metrika (IF 0.679) Pub Date : 2020-06-05
Qibing Gao, Xiuqing Zhou, Yanqin Feng, Xiuli Du, XiaoXiao Liu

An estimation for censored quantile regression models, which is based on an inverse-censoring-probability weighting method, is studied in this paper, and asymptotic distribution of the parameter vector estimator is obtained. Based on the parameter estimation and asymptotic distribution of the estimator, an empirical likelihood inference method is proposed for censored quantile regression models and

更新日期：2020-06-05
• Metrika (IF 0.679) Pub Date : 2020-06-05
Rakhi Singh, Joachim Kunert

Crossover designs are called for in situations when several subjects undergo a sequence of treatments. Though, usually, the model contains the direct effects of treatments as well as the carryover effects, the primary interest lies in the estimation of direct effects of the treatment. Most results in the literature on crossover designs are available for the situations where either the number of periods

更新日期：2020-06-05
• Metrika (IF 0.679) Pub Date : 2020-05-28

For the special case of balanced one-way random effects ANOVA, it has been established that the generalized likelihood ratio test (LRT) and Wald’s test are largely equivalent in testing the variance component. We extend these results to explore the relationships between Wald’s F test, and the LRT for a much broader class of linear mixed models; the generalized split-plot models. In particular, we explore

更新日期：2020-05-28
• Metrika (IF 0.679) Pub Date : 2020-05-20
Yeşim Güney, Y. Tuaç, Ş. Özdemir, O. Arslan

In this article, we consider the parameter estimation of regression model with pth-order autoregressive (AR(p)) error term. We use the maximum Lq-likelihood (MLq) estimation method proposed by Ferrari and Yang (Ann Stat 38(2):753–783, 2010), as a robust alternative to the classical maximum likelihood (ML) estimation method to handle the outliers in the data. After exploring the MLq estimators for the

更新日期：2020-05-20
• Metrika (IF 0.679) Pub Date : 2020-04-30
Hyunju Lee, Ji Hwan Cha

In this paper, we develop a general multivariate new better than used (MNBU) distribution based on a multivariate common shock model. Assuming that the external shock process follows the generalized Pólya process and a shock can destroy each component with some given probability, the multivariate survival distribution is obtained. The dependence structure of the multivariate distribution is analyzed

更新日期：2020-04-30
• Metrika (IF 0.679) Pub Date : 2020-01-01

Measuring the correlation between two random variables is an important goal in various statistical applications. The standardized covariance is a widely used criterion for measuring the linear association. In this paper, first, we propose a covariance-based unified measure of variability for a continuous random variable X and show that several measures of variability and uncertainty, such as variance

更新日期：2020-01-01
• Metrika (IF 0.679) Pub Date : 2019-12-18
Nengxiang Ling, Lingyu Wang, Philippe Vieu

We investigate kernel estimates in the functional nonparametric regression model when both the response and the explanatory variable (the covariate) are functional. The rates of almost complete and uniform almost complete convergence of the estimator are obtained under some mild $$\alpha$$-mixing functional sample. Finally, a simulation study is carried out to illustrate the finite sample performance

更新日期：2019-12-18
• Metrika (IF 0.679) Pub Date : 2019-12-04
Antonia Castaño-Martínez, Gema Pigueiras, Georgios Psarrakos, Miguel A. Sordo

We provide in this paper sufficient conditions for comparing, in terms of the increasing concave order, some income random variables based on linear combinations of order statistics that are relevant in the framework of social welfare. The random variables under study are weighted average incomes of the poorest and, for some particular weights, their expectations are welfare measures whose integral

更新日期：2019-12-04
• Metrika (IF 0.679) Pub Date : 2019-11-05
Achintya Roy, Nitin Gupta

In this paper, we focus on a particular type of coherent system which may fail either on the failure of its first component or on the failure of its second component. We investigate the renewal of such a coherent system using two cold standby components. We obtain the reliability function of the considered coherent system which is equipped with two cold standby components. We study the problem to optimize

更新日期：2019-11-05
• Metrika (IF 0.679) Pub Date : 2015-07-15
Edsel A Peña,Joshua D Habiger,Wensong Wu

Two general classes of multiple decision functions, where each member of the first class strongly controls the family-wise error rate (FWER), while each member of the second class strongly controls the false discovery rate (FDR), are described. These classes offer the possibility that optimal multiple decision functions with respect to a pre-specified Type II error criterion, such as the missed discovery

更新日期：2019-11-01
• Metrika (IF 0.679) Pub Date : 2010-03-04
Albert Vexler,Chengqing Wu,Kai Fun Yu

We propose and examine statistical test-strategies that are somewhat between the maximum likelihood ratio and Bayes factor methods that are well addressed in the literature. The paper shows an optimality of the proposed tests of hypothesis. We demonstrate that our approach can be easily applied to practical studies, because execution of the tests does not require deriving of asymptotical analytical

更新日期：2019-11-01
• Metrika (IF 0.679) Pub Date : 2009-03-01
James Robins,Lingling Li,Eric Tchetgen,Aad W van der Vaart

We discuss a new method of estimation of parameters in semiparametric and nonparametric models. The method is based on U-statistics constructed from quadratic influence functions. The latter extend ordinary linear influence functions of the parameter of interest as defined in semiparametric theory, and represent second order derivatives of this parameter. For parameters for which the matching cannot

更新日期：2019-11-01
• Metrika (IF 0.679) Pub Date : 2019-10-24

We model an overdispersed count as a dependent measurement, by means of the Negative Binomial distribution. We consider a quantitative covariate that is fixed by design. The expectation of the dependent variable is assumed to be a known function of a linear combination involving the possibly multidimensional covariate and its coefficients. In the NB1-parametrization of the Negative Binomial distribution

更新日期：2019-10-24
• Metrika (IF 0.679) Pub Date : 2019-10-12
Yuichi Goto, Masanobu Taniguchi

Binary time series can be derived from an underlying latent process. In this paper, we consider an ellipsoidal alpha mixing strictly stationary process and discuss the discriminant analysis and propose a classification method based on binary time series. Assume that the observations are generated by time series which belongs to one of two categories described by different spectra. We propose a method

更新日期：2019-10-12
• Metrika (IF 0.679) Pub Date : 2019-10-09
Longxiang Fang, Wenyu Huang

In this paper, we investigate two inequalities based on majorization for two random vectors with different Gaussian marginals and the same underlying Archimedean copulas. The established inequalities generalize well-known results by Slepian.

更新日期：2019-10-09
• Metrika (IF 0.679) Pub Date : 2019-09-24
Rafał Połoczański, Maciej Wilczyński

The problem of estimating a bivariate cumulative distribution function F under the weighted squared error loss and the weighted Cramer–von Mises loss is considered. No restrictions are imposed on the unknown function F. Estimators, which are minimax among procedures being affine transformation of the bivariate empirical distribution function, are found. Then it is proved that these procedures are minimax

更新日期：2019-09-24
• Metrika (IF 0.679) Pub Date : 2019-09-09
Min-Jue Zhang, Rong-Xian Yue

This paper considers constructions of optimal designs for heteroscedastic polynomial measurement error models. Corresponding approximate design theory is developed by using corrected score function approach, which leads to non-concave optimisation problems. For the weighted polynomial measurement error model of degree p with some commonly used heteroscedastic structures, the upper bounds for the number

更新日期：2019-09-09
• Metrika (IF 0.679) Pub Date : 2019-09-07
Xianwen Ding, Jiandong Chen, Xueping Chen

The paper concerns the regularized quantile regression for ultrahigh-dimensional data with responses missing not at random. The propensity score is specified by the semiparametric exponential tilting model. We use the Pearson Chi-square type test statistic for identification of the important features in the sparse propensity score model, and employ the adjusted empirical likelihood method for estimation

更新日期：2019-09-07
• Metrika (IF 0.679) Pub Date : 2019-08-27
Hongyi Li, Hong Qin

Fractional factorial designs are widely used because of their various merits. Foldover or level permutation are usually used to construct optimal fractional factorial designs. In this paper, a novel method via foldover and level permutation, called quadrupling, is proposed to construct uniform four-level designs with large run sizes. The relationship of uniformity between the initial design and the

更新日期：2019-08-27
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