当前期刊: Statistics Go to current issue    加入关注    本刊投稿指南
显示样式:        排序: IF: - GO 导出
我的关注
我的收藏
您暂时未登录!
登录
  • On Liu-type biased estimators in measurement error models
    Statistics (IF 0.645) Pub Date : 2020-12-28
    A. K. Md. Ehsanes Saleh; Shalabh

    ABSTRACT This paper considers the shrinkage estimation of parameters of measurement error models when it is suspected that the parameters may belong to a linear subspace. The class of Liu type estimators is proposed by choosing five quasi-empirical Bayes estimators in the presence of measurement errors in the data. This class of estimator combines the sample and prior information together along with

    更新日期:2021-01-13
  • Asymptotic properties for the estimators in heteroscedastic semiparametric EV models with α-mixing errors
    Statistics (IF 0.645) Pub Date : 2021-01-06
    Mengmei Xi; Rui Wang; Wei Yu; Yan Shen; Xuejun Wang

    ABSTRACT In this paper, the heteroscedastic semiparametric errors-in-variables (EV) model, y i = ξ i β + g ( t i ) + ϵ i , x i = ξ i + μ i , 1 ≤ i ≤ n , is considered, where ϵ i = σ i e i , σ i 2 = f ( u i ) , β is an unknown parameter to be estimated and g ( ⋅ ) and f ( ⋅ ) are unknown functions to be estimated. Under some suitable conditions, asymptotic properties for the estimators of β, g ( ⋅ )

    更新日期:2021-01-13
  • Semi-parametric adjustment to computer models
    Statistics (IF 0.645) Pub Date : 2020-12-17
    Yan Wang; Rui Tuo

    Computer simulations are widely used in scientific exploration and engineering designs. However, computer outputs usually do not match the reality perfectly because the computer models are built under certain simplifications and approximations. When physical observations are also available, statistical methods can be applied to estimate the discrepancy between the computer output and the physical response

    更新日期:2021-01-13
  • Robust estimation with modified Huber's function for functional linear models
    Statistics (IF 0.645) Pub Date : 2020-12-23
    Xiong Cai; Liugen Xue; Zhaoliang Wang

    In this article, we consider a new robust estimation procedure for functional linear models with both slope function and functional predictor approximated by functional principal component basis functions. A modified Huber's function with tail function substituted by the exponential squared loss (ESL) is applied to the estimation procedure for achieving robustness against outliers. The tuning parameters

    更新日期:2021-01-13
  • Evidence for goodness of fit in Karl Pearson chi-squared statistics
    Statistics (IF 0.645) Pub Date : 2021-01-07
    R. G. Staudte

    ABSTRACT Chi-squared tests for lack of fit are traditionally employed to find evidence against a hypothesized model, with the model accepted if the Karl Pearson statistic comparing observed and expected numbers of observations falling within cells is not significantly large. However, if one really wants evidence for goodness of fit, it is better to adopt an equivalence testing approach in which small

    更新日期:2021-01-13
  • An extension of the Cox–Czanner divergence measure to residual lifetime distributions with applications
    Statistics (IF 0.645) Pub Date : 2020-12-23
    Zahra Mansourvar; Majid Asadi

    A time-dependent divergence measure is proposed to compare the survival functions of two lifetime random variables. It is shown that the proposed measure ranges between [ 0 , 1 ] and for the proportional hazards case has the metric properties. Several properties of the divergence measure are investigated, among others, it is shown that the divergence between two survival functions does not depend on

    更新日期:2021-01-13
  • Modelling count data via copulas
    Statistics (IF 0.645) Pub Date : 2021-01-08
    Hadi Safari-Katesari; S. Yaser Samadi; Samira Zaroudi

    Copula models have been widely used to model the dependence between continuous random variables, but modelling count data via copulas has recently become popular in the statistics literature. Spearman's rho is an appropriate and effective tool to measure the degree of dependence between two random variables. In this paper, we derive the population version of Spearman's rho via copulas when both random

    更新日期:2021-01-13
  • Modelling count data via copulas
    Statistics (IF 0.645) Pub Date : 2021-01-08
    Hadi Safari-Katesari; S. Yaser Samadi; Samira Zaroudi

    Copula models have been widely used to model the dependence between continuous random variables, but modelling count data via copulas has recently become popular in the statistics literature. Spearman's rho is an appropriate and effective tool to measure the degree of dependence between two random variables. In this paper, we derive the population version of Spearman's rho via copulas when both random

    更新日期:2021-01-08
  • Evidence for goodness of fit in Karl Pearson chi-squared statistics
    Statistics (IF 0.645) Pub Date : 2021-01-07
    R. G. Staudte

    ABSTRACT Chi-squared tests for lack of fit are traditionally employed to find evidence against a hypothesized model, with the model accepted if the Karl Pearson statistic comparing observed and expected numbers of observations falling within cells is not significantly large. However, if one really wants evidence for goodness of fit, it is better to adopt an equivalence testing approach in which small

    更新日期:2021-01-07
  • Asymptotic properties for the estimators in heteroscedastic semiparametric EV models with α-mixing errors
    Statistics (IF 0.645) Pub Date : 2021-01-06
    Mengmei Xi; Rui Wang; Wei Yu; Yan Shen; Xuejun Wang

    ABSTRACT In this paper, the heteroscedastic semiparametric errors-in-variables (EV) model, y i = ξ i β + g ( t i ) + ϵ i , x i = ξ i + μ i , 1 ≤ i ≤ n , is considered, where ϵ i = σ i e i , σ i 2 = f ( u i ) , β is an unknown parameter to be estimated and g ( ⋅ ) and f ( ⋅ ) are unknown functions to be estimated. Under some suitable conditions, asymptotic properties for the estimators of β, g ( ⋅ )

    更新日期:2021-01-06
  • Semi-parametric adjustment to computer models
    Statistics (IF 0.645) Pub Date : 2020-12-17
    Yan Wang; Rui Tuo

    Computer simulations are widely used in scientific exploration and engineering designs. However, computer outputs usually do not match the reality perfectly because the computer models are built under certain simplifications and approximations. When physical observations are also available, statistical methods can be applied to estimate the discrepancy between the computer output and the physical response

    更新日期:2020-12-17
  • A block bootstrap for quasi-likelihood in sparse functional data
    Statistics (IF 0.645) Pub Date : 2020-10-16
    Guangbao Guo

    This article utilizes bootstrap quasi-likelihood (QL) to model sparse functional data. The proposed method combines parallel block bootstrap and QL to fit the functional data. The parameter space is considered as a finite-dimensional space through a certain optimization rule. Statistical errors of the proposed method are discussed. Some asymptotic properties of the method are established under several

    更新日期:2020-11-23
  • A uniform-in-P Edgeworth expansion under weak Cramér conditions
    Statistics (IF 0.645) Pub Date : 2020-10-30
    Kyungchul Song

    This paper provides a finite sample bound for the error term in the Edgeworth expansion for a sum of independent, potentially discrete, non-lattice random vectors, using a uniform-in-P version of the weaker Cramér condition in [Angst J, Poly G. A Weak Cramèr Condition and Application to Edgeworth Expansions. Electronic J Prob. 2017;22:1–24]. This finite sample bound can be used to derive an Edgeworth

    更新日期:2020-11-23
  • Best prediction regions for future exponential record intervals
    Statistics (IF 0.645) Pub Date : 2020-10-02
    Elham Basiri; Arturo J. Fernández; Akbar Asgharzadeh; Seyed Fazel Bagheri

    A class of prediction regions for a future upper record interval ( R s , R l ) based on a type-II censored sample from the exponential distribution is presented in this paper. The best prediction region for ( R s , R l ) is then determined by solving a constrained nonlinear optimization problem. The objective function is the area of the prediction region and the constraints are related to the desired

    更新日期:2020-11-23
  • Relative stochastic orders of weighted frailty models
    Statistics (IF 0.645) Pub Date : 2020-11-11
    Xu He; Hongmei Xie

    ABSTRACT In this paper, relative stochastic comparisons of weighted frailty models with respect to relative hazard rate and relative mean residual life orders are considered. Some closure properties of the model in two relative stochastic orders sense are presented. Under some appropriate assumptions, we show how the variation of the frailty variable and the variation of the baseline variable translate

    更新日期:2020-11-23
  • On strong consistency and asymptotic normality of one-step Gauss-Newton estimators in ARMA time series models
    Statistics (IF 0.645) Pub Date : 2020-10-12
    Pierre Duchesne; Pierre Lafaye de Micheaux; Joseph François Tagne Tatsinkou

    ABSTRACT One-step Gauss-Newton estimators for causal and invertible autoregressive moving-average (ARMA) time series models with an unknown mean are considered. A proof of the strong consistency and asymptotic normality of these estimators is provided. In a simulation study, their empirical properties are illustrated in ARMA models and compared to a other estimators: the estimators based on the innovations

    更新日期:2020-11-23
  • A multi-scale approach for testing and detecting peaks in time series
    Statistics (IF 0.645) Pub Date : 2020-10-22
    Michael Messer; Hendrik Backhaus; Ting Fu; Albrecht Stroh; Gaby Schneider

    ABSTRACT An approach is presented that combines a statistical test for peak detection with the estimation of peak positions in time series. Motivated by empirical observations in neuronal recordings, we aim at investigating peaks of different heights and widths. We use a moving window approach to compare the differences of estimated slope coefficients of local regression models. We combine multiple

    更新日期:2020-11-23
  • The sparse variance contamination model
    Statistics (IF 0.645) Pub Date : 2020-09-22
    Ery Arias-Castro; Rong Huang

    We consider a Gaussian contamination (i.e., mixture) model where the contamination manifests itself as a change in variance. We study this model in various asymptotic regimes, in parallel with the work of Ingster YI. [Some problems of hypothesis testing leading to infinitely divisible distributions. Math Methods Stat. 1997;6(1):47–69] and Donoho D, Jin J. [Higher criticism for detecting sparse heterogeneous

    更新日期:2020-11-23
  • A robust multivariate Birnbaum–Saunders regression model
    Statistics (IF 0.645) Pub Date : 2020-10-22
    Renata G. Romeiro; Filidor Vilca; N. Balakrishnan; Camila Borelli Zeller

    ABSTRACT This work presents a log-linear model for multivariate Birnbaum–Saunders distribution that can be used in survival analysis to investigate correlated log-lifetimes of two or more units. This model is studied through the use of a generalized multivariate sinh-normal distribution, which is built from the multivariate mixture scale of normal distributions. The marginal and conditional linear

    更新日期:2020-11-23
  • Adaptive elastic-net selection in a quantile model with diverging number of variable groups
    Statistics (IF 0.645) Pub Date : 2020-10-08
    Gabriela Ciuperca

    In real applications of the linear model, the explanatory variables are very often naturally grouped, the most common example being the multivariate variance analysis. In the present paper, a quantile model with group structure is considered, where the number of groups can diverge with the sample size. We introduce and study the adaptive elastic-net group quantile estimator, for improving the parameter

    更新日期:2020-11-23
  • Penalized empirical likelihood for high-dimensional partially linear errors-in-function model with martingale difference errors
    Statistics (IF 0.645) Pub Date : 2020-10-30
    HE Bang-Qiang; LV Sheng-Ri

    ABSTRACT For the high-dimensional partially linear errors-in-function model with martingale difference errors, we, in this paper, propose an empirical log-likelihood ratio function for the regression parameter. The empirical log-likelihood ratio is proven to be asymptotically chi-squared. In addition, we propose penalized empirical likelihood (PEL) for the parameter. By using an appropriate penalty

    更新日期:2020-10-30
  • On jackknifing the symmetrized Tyler matrix
    Statistics (IF 0.645) Pub Date : 2020-09-29
    František Rublík

    The consistency of the jackknife estimator of the asymptotic covariance matrix of a differentiable function of the symmetrized Tyler matrix is proved for sampling from continuous distribution without any constraint on this sampled continuous distribution. It is shown that under mild regularity conditions the rank of the asymptotic covariance matrix attains maximum possible value. The results are applied

    更新日期:2020-09-29
  • Optimal equivariant prediction regions based on multiply type-II censored generalized order statistics from exponential distributions
    Statistics (IF 0.645) Pub Date : 2020-09-02
    Grigoriy Volovskiy; Udo Kamps

    Interval prediction of future generalized order statistics from exponential distributions based on a multiply Type-II censored sample is considered. On invoking the principle of reduction by equivariance, prediction regions of minimal size are derived and shown to be of interval form. An alternative derivation based on the use of a prediction sufficient statistic is pointed out.

    更新日期:2020-09-02
  • Trend-transformed independent vectors: construction and stochastic comparison results
    Statistics (IF 0.645) Pub Date : 2020-08-14
    F. G. Badía; Sophie Mercier; C. Sangüesa

    A new class of random vectors is introduced, where the components are obtained through trend-transforms of independent random variables. Such a vector is called trend-transformed independent vector. The new class includes many models from the previous literature, such as sequential and intermediate order statistics, or the vectors formed by the first arrival times in classical counting processes such

    更新日期:2020-09-01
  • On numbers of observations in random regions determined by records
    Statistics (IF 0.645) Pub Date : 2020-06-30
    Anna Dembińska; Masoumeh Akbari; Jafar Ahmadi

    Near-record observations are the ones that occur between successive record times and within a fixed distance of the current record value. In this paper, the concept of near-record observations is generalized to the notion of observations that fall into a random region determined by a given record and a Borel set. Description of the distribution of the number of such observations is provided, and asymptotic

    更新日期:2020-09-01
  • Almost sure limit behaviour of Pfeifer record values
    Statistics (IF 0.645) Pub Date : 2020-08-05
    Jacob Peter Schmidt; Udo Kamps

    Pfeifer record values are based on a double sequence of independent, non-identically distributed random variables. For Pfeifer records with a common baseline distribution function and depending on a sequence of positive parameters, almost sure convergence to a non-degenerate random variable is examined, and sufficient conditions for almost sure relative stability as well as related results are studied

    更新日期:2020-09-01
  • Ordered maximum ranked set sampling with unequal sample
    Statistics (IF 0.645) Pub Date : 2020-08-19
    Mehdi Basikhasteh; Fazlollah Lak; Saeid Tahmasebi

    In this paper, a new sampling method is introduced by ordering the maxima of ranked set samples with unequal sizes. In this new modification of ranked set sampling which is called OMRSSU, the pdf, cdf and joint pdf are obtained. Also, a new distribution-free prediction interval for future order statistics is derived. In addition, the moments of OMRSSU for exponential distribution are computed and then

    更新日期:2020-09-01
  • The limiting distribution of combining the t and Wilcoxon rank sum tests
    Statistics (IF 0.645) Pub Date : 2020-08-24
    Masato Kitani; Hidetoshi Murakami

    In two-sample testing problems, Student's t-test and the Wilcoxon rank-sum test are often used to test the location parameter, and have been discussed by many authors over the years. The Wilcoxon rank-sum test is more powerful than the t-test for non-normal data. Previous studies consider combining these two tests within a maximum test and show that it controls the type I error and has good statistical

    更新日期:2020-09-01
  • Recruitment and survival time under mean residual lifetime bias sampling
    Statistics (IF 0.645) Pub Date : 2020-08-12
    Polychronis Economou; Georgios Psarrakos; Abdolsaeed Toomaj

    There are several situations in which we can assume that an individual with larger mean residual lifetime is more likely to participate in a sample than another with smaller mean residual lifetime; for example, employment agencies are more likely to hire individuals that are not close to their retirement. In this paper, a new bivariate model is proposed to describe such situations by modelling the

    更新日期:2020-09-01
  • Uniform convergence rate of the nonparametric maximum likelihood estimator for current status data with competing risks
    Statistics (IF 0.645) Pub Date : 2020-08-28
    Sergey V. Malov

    We study the uniform convergence rate of the nonparametric maximum likelihood estimator (MLE) for the sub-distribution functions of failure times in the current status data with competing risks model. It is known that the MLE have L 2 -norm convergence rate O P ( n − 1 / 3 ) in the absolutely continuous case, but no agreement has emerged on a uniform convergence rate. We specify conditions under which

    更新日期:2020-08-28
  • A self-consistent estimator for interval-valued data
    Statistics (IF 0.645) Pub Date : 2020-08-28
    Hyejeong Choi; Johan Lim; Xinlei Wang; Minjung Kwak

    In interval-valued data, the variable of interest is provided in the form of an interval with lower and upper bounds, not a single value. An univariate representation for the interval is not unique by its nature, in particular when interval-valued data are of the min-max (MM) type. Researchers focus on the marginal histogram distribution which is well suited to the measurement error (ME) type interval

    更新日期:2020-08-28
  • Testing in the growth curve model with intraclass correlation structure
    Statistics (IF 0.645) Pub Date : 2020-08-25
    Veronika Jurková; Ivan Žežula; Daniel Klein

    This paper describes two tests in the growth curve model under multivariate normality. The first one is revisited test for intraclass structure of the covariance matrix, and the second one is the simultaneous test for intraclass covariance structure together with a specific mean value of the model. Both tests are likelihood ratio tests.

    更新日期:2020-08-25
  • Efficient estimation for the non-mixture cure model with current status data
    Statistics (IF 0.645) Pub Date : 2020-06-22
    Xiaoguang Wang; Bo Han

    Medical advances including the neoadjuvant anti-PD-1 immunotherapy play a role in promoting clinical outcomes such as improved overall and progression-free survival probabilities. This paper considers the regression analysis of current status data with a cured subgroup in the population using a semiparametric non-mixture cure model. We propose a sieve maximum likelihood estimation for the model with

    更新日期:2020-06-22
  • Exponentiality tests based on Basu characterization
    Statistics (IF 0.645) Pub Date : 2020-06-04
    M. D. Jiménez-Gamero; Bojana Milošević; Marko Obradović

    This paper proposes and studies two new classes of tests for exponentiality. Both of them are based on Basu's characterization of the exponential distribution. The null distributions of the test statistics are parameter free. Moreover, conveniently normalized, they are asymptotically normally distributed. The large sample behaviour of the proposed tests is studied for fixed alternatives, and for local

    更新日期:2020-06-04
  • Testing Kendall's τ for a large class of dependent sequences
    Statistics (IF 0.645) Pub Date : 2020-06-02
    Sinda Ammous

    Let ( X i , Y i ) i ∈ Z be a stationary sequence of R 2 -valued random variables. To test if X 1 and Y 1 are correlated in the sense of Kendall, we propose a robust correction of the usual Kendall test, valid for a large class of dependent sequences. We also show that the condition on the dependency coefficients is quasi-optimal in a certain sense, and we illustrate our results trough different sets

    更新日期:2020-06-02
  • A jackknifed ridge estimator in probit regression model
    Statistics (IF 0.645) Pub Date : 2020-06-01
    Yasin Asar; Kadriye Kılınç

    In this study, the effects of multicollinearity on the maximum likelihood estimator are analyzed in the probit regression model. It is known that the near-linear dependencies in the design matrix affect the maximum likelihood estimation negatively, namely, the standard errors become so large so that the estimations are said to be inconsistent. Therefore, a new jackknifed ridge estimator is introduced

    更新日期:2020-06-01
  • Stochastic comparisons on sample extremes from independent or dependent gamma samples
    Statistics (IF 0.645) Pub Date : 2020-06-01
    Rui Fang; Boyang Wang

    This study deals with random variables from gamma samples. For independent samples, it is found that when all the shape parameters are not smaller than 1, a less weakly supermajorized shape parameter vector implies a larger sample minimum in the sense of the hazard rate order. When the shape parameters are the same, a less weakly submajorized scale parameter vector also leads to a larger sample minimum

    更新日期:2020-06-01
  • Limit theorems for univariate and bivariate order statistics with variable ranks
    Statistics (IF 0.645) Pub Date : 2020-05-28
    H. M. Barakat; E. M. Nigm; M. H. Harpy

    In this work, we investigate the asymptotic behaviour of the intermediate and central order statistics of a bivariate data by using the Reduced Ordering Principle (R-ordering). When, the sup-norm is used, we reveal the interrelation between the R-ordering principle and Marginal-Ordering Principle (M-ordering). The asymptotic behaviour of the intermediate and central bivariate order statistics based

    更新日期:2020-05-28
  • Quantile regression for doubly truncated data
    Statistics (IF 0.645) Pub Date : 2020-05-28
    Pao-sheng Shen

    Doubly truncated data arise when the event time of interest T is observed only if it falls within a subject-specific, possibly random, interval [ U , V ] . In this article, we study the problem of fitting a quantile regression model with doubly truncated data. Based on the non-parametric maximum likelihood estimator of K ( t ) = P ( U < t < V ) , we proposed a weighted quantile regression estimator

    更新日期:2020-05-28
  • On the rates of convergence of parallelized averaged stochastic gradient algorithms
    Statistics (IF 0.645) Pub Date : 2020-05-18
    Antoine Godichon-Baggioni; Sofiane Saadane

    The growing interest for high-dimensional and functional data analysis led in the last decade to important research developing a consequent amount of techniques. Parallelized algorithms, which consist of distributing and treat the data into different machines, for example, are a good answer to deal with large samples taking values in high-dimensional spaces. We introduce here a parallelized averaged

    更新日期:2020-05-18
  • Uncertain stochastic ridge estimation in partially linear regression models with elliptically distributed errors
    Statistics (IF 0.645) Pub Date : 2020-05-14
    Mahdi Roozbeh; Nor Aishah Hamzah

    In fitting a regression model to survey data, using additional information or prior knowledge, stochastic uncertainty occurs in specifying linear programming due to economic and financial studies. These stochastic constraints, definitely cause some changes in the classic estimators and their efficiencies. In this paper, stochastic shrinkage estimators and their positive parts are defined in the partially

    更新日期:2020-05-14
  • A bimodal gamma distribution: properties, regression model and applications
    Statistics (IF 0.645) Pub Date : 2020-05-13
    Roberto Vila; Letícia Ferreira; Helton Saulo; Fábio Prataviera; Edwin Ortega

    In this paper, we propose a bimodal gamma distribution using a quadratic transformation based on the alpha-skew-normal model. We discuss several properties of this distribution such as mean, variance, moments, hazard rate and entropy measures. Further, we propose a new regression model with censored data based on the bimodal gamma distribution. This regression model can be very useful to the analysis

    更新日期:2020-05-13
  • Exact likelihood-ratio tests for joint type-II censored exponential data
    Statistics (IF 0.645) Pub Date : 2020-05-13
    Xiaojun Zhu; N. Balakrishnan; Chengzhu Feng; Jiacheng Ni; Nanxi Yu; Weilin Zhou

    Several results based on the likelihood-ratio test have been discussed in the literature for testing the scale parameters of two exponential distributions under complete and different censored forms of data, many of which are asymptotic in nature. However, exact likelihood-ratio tests have been derived only for the case of complete and independent Type-II censored samples. In this paper, we first develop

    更新日期:2020-05-13
  • A bimodal gamma distribution: properties, regression model and applications
    Statistics (IF 0.645) Pub Date : 2020-05-13
    Roberto Vila; Letícia Ferreira; Helton Saulo; Fábio Prataviera; Edwin Ortega

    In this paper, we propose a bimodal gamma distribution using a quadratic transformation based on the alpha-skew-normal model. We discuss several properties of this distribution such as mean, variance, moments, hazard rate and entropy measures. Further, we propose a new regression model with censored data based on the bimodal gamma distribution. This regression model can be very useful to the analysis

    更新日期:2020-05-13
  • Exact likelihood-ratio tests for joint type-II censored exponential data
    Statistics (IF 0.645) Pub Date : 2020-05-13
    Xiaojun Zhu; N. Balakrishnan; Chengzhu Feng; Jiacheng Ni; Nanxi Yu; Weilin Zhou

    Several results based on the likelihood-ratio test have been discussed in the literature for testing the scale parameters of two exponential distributions under complete and different censored forms of data, many of which are asymptotic in nature. However, exact likelihood-ratio tests have been derived only for the case of complete and independent Type-II censored samples. In this paper, we first develop

    更新日期:2020-05-13
  • Ordering results of extreme order statistics from heterogeneous Gompertz–Makeham random variables
    Statistics (IF 0.645) Pub Date : 2020-04-07
    Priyanka Majumder; Shyamal Ghosh; Murari Mitra

    Gompertz–Makeham distribution, which is not a member of the location-scale family, has been widely used for describing human mortality, determining policies in insurance, establishing actuarial tables and growth models. In this paper, we study stochastic comparisons for extreme order statistics from independent heterogeneous Gompertz–Makeham samples. The comparisons are carried out in the sense of

    更新日期:2020-04-07
  • Projection-based classification for functional data
    Statistics (IF 0.645) Pub Date : 2020-04-07
    Nadiyeh Darabi; S. Mohammad E. Hosseini-Nasab

    The classification of functional data has many applications in a variety of problems. A popular method for functional data classification is based on distances of the observations to the class centroid. In this paper, we introduce a weighted version of the centroid classifier that is based on projection functions and can lead to asymptotically perfect classification. We select the projection functions

    更新日期:2020-04-07
  • Identifiability of parameters in longitudinal correlated Poisson and inflated beta regression model with non-ignorable missing mechanism
    Statistics (IF 0.645) Pub Date : 2020-04-03
    Elham Tabrizi; Ehsan Bahrami Samani; Mojtaba Ganjali

    The identifiability of a statistical model is an essential and necessary property. When a model is not identifiable, even an infinite number of observations cannot determine the true parameter. Non-identifiablity problem in generalized linear models with and without random effects is very common. Also it can occur in such models when the response variable has non-ignorably missing. Since the structure

    更新日期:2020-04-03
  • Copula versions of distance multivariance and dHSIC via the distributional transform – a general approach to construct invariant dependence measures
    Statistics (IF 0.645) Pub Date : 2020-04-01
    Björn Böttcher

    The multivariate Hilbert-Schmidt Independence Criterion (dHSIC) and distance multivariance allow to measure and test independence of an arbitrary number of random vectors with arbitrary dimensions. Here, we define versions which only depend on an underlying copula. The approach is based on the distributional transform, yielding dependence measures which always feature a natural invariance with respect

    更新日期:2020-04-01
  • Ensuring balance through optimal allocation of experimental units with known categorical covariates into two treatments
    Statistics (IF 0.645) Pub Date : 2020-03-24
    Samrat Hore; Anup Dewanji; Aditya Chatterjee

    The balanced allocation of experimental units with regard to various known covariates among several treatment groups, before the physical experiment takes place, is often considered to be the most reasonable allocation scheme in all intervention studies and clinical trials. It is well-known that covariate mean balance over various treatment groups ensures widely used D- and A-optimality. However, it

    更新日期:2020-03-24
  • Semiparametric regression using empirical likelihood with shape information
    Statistics (IF 0.645) Pub Date : 2020-03-13
    Weibin Zhong; Kepher H. Makambi; Ao Yuan

    The empirical likelihood is a popular tool in statistics and many other fields, including regression analysis. It has the advantage of robustness against model specification and can incorporate side information to improve the estimation accuracy. There is vast literature on empirical likelihood incorporating various side information, mostly in the form of moment constraint(s). Here we study this method

    更新日期:2020-03-13
  • Constructing optimal projection designs
    Statistics (IF 0.645) Pub Date : 2019-11-12
    A. M. Elsawah, Yu Tang, Kai-Tai Fang

    The early stages of many real-life experiments involve a large number of factors among which only a few factors are active. Unfortunately, the optimal full-dimensional designs of those early stages may have bad low-dimensional projections and the experimenters do not know which factors turn out to be important before conducting the experiment. Therefore, designs with good projections are desirable

    更新日期:2019-11-12
  • Exact inference on multiple exponential populations under a joint type-II progressive censoring scheme
    Statistics (IF 0.645) Pub Date : 2019-11-05
    Shuvashree Mondal, Debasis Kundu

    Recently Mondal and Kundu [Mondal S, Kundu D. A new two sample type-II progressive censoring scheme. Commun Stat Theory Methods. 2018. doi:10.1080/03610926.2018.1472781] introduced a Type-II progressive censoring scheme for two populations. In this article, we extend the above scheme for more than two populations. The aim of this paper is to study the statistical inference under the multi-sample Type-II

    更新日期:2019-11-05
  • On an asymptotic relative efficiency concept based on expected volumes of confidence regions
    Statistics (IF 0.645) Pub Date : 2019-11-05
    Ludwig Baringhaus, Daniel Gaigall

    The paper deals with an asymptotic relative efficiency concept for confidence regions of multidimensional parameters that is based on the expected volumes of the confidence regions. Under standard conditions the asymptotic relative efficiencies of confidence regions are seen to be certain powers of the ratio of the limits of the expected volumes. These limits are explicitly derived for confidence regions

    更新日期:2019-11-05
  • Testing the homogeneity of risk differences with sparse count data
    Statistics (IF 0.645) Pub Date : 2019-10-10
    Junyong Park, Iris Ivy Gauran

    In this paper, we consider testing the homogeneity of risk differences in independent binomial distributions especially when data are sparse. We point out some drawback of existing tests in either controlling a nominal size or obtaining powers through theoretical and numerical studies. The proposed test is designed to avoid the drawbacks of existing tests. We present the asymptotic null distribution

    更新日期:2019-10-10
  • A pivot function and its limiting distribution: applications in goodness of fit and testing hypothesis
    Statistics (IF 0.645) Pub Date : 2019-10-01
    A. R. Soltani

    In this paper, a pivot function which is in terms of the sample and the underlying population distribution is introduced. It is assumed that the population distribution is continuous and strictly increasing on its support. Then, the martingale central limit theorem is applied to prove that limiting distribution of the pivot function is the standard normal. Interestingly, this result provides a unified

    更新日期:2019-10-01
  • Principal varying coefficient estimator for high-dimensional models
    Statistics (IF 0.645) Pub Date : 2019-09-16
    Weihua Zhao, Fode Zhang, Xuejun Wang, Rui Li, Heng Lian

    We consider principal varying coefficient models in the high-dimensional setting, combined with variable selection, to reduce the effective number of parameters in semiparametric modelling. The estimation is based on B-splines approach. For the unpenalized estimator, we establish non-asymptotic bounds of the estimator and then establish the (asymptotic) local oracle property of the penalized estimator

    更新日期:2019-09-16
  • Simultaneous confidence bands for growth incidence curves in weighted sup-norm metrics
    Statistics (IF 0.645) Pub Date : 2019-09-04
    Biyi Shen, Fabian Dunker, Chixiang Chen

    The so-called growth incidence curve (GIC) is a popular way to evaluate the distributional pattern of economic growth and pro-poorness of growth in development economics. The log-transformation of the the GIC is related to the sum of empirical quantile processes which allows for constructions of simultaneous confidence bands for the GIC. However, standard constructions of these bands tend to be too

    更新日期:2019-09-04
  • Large-scale multiple hypothesis testing with the normal-beta prime prior
    Statistics (IF 0.645) Pub Date : 2019-09-02
    Ray Bai, Malay Ghosh

    We revisit the problem of simultaneously testing the means of n independent normal observations under sparsity. We take a Bayesian approach to this problem by studying a scale-mixture prior known as the normal-beta prime (NBP) prior. To detect signals, we propose a hypothesis test based on thresholding the posterior shrinkage weight under the NBP prior. Taking the loss function to be the expected number

    更新日期:2019-09-02
  • Model fusion and multiple testing in the likelihood paradigm: shrinkage and evidence supporting a point null hypothesis
    Statistics (IF 0.645) Pub Date : 2019-08-30
    David R. Bickel, Abbas Rahal

    According to the general law of likelihood, the strength of statistical evidence for a hypothesis as opposed to its alternative is the ratio of their likelihoods, each maximized over the parameter of interest. Consider the problem of assessing the weight of evidence for each of several hypotheses. Under a realistic model with a free parameter for each alternative hypothesis, this leads to weighing

    更新日期:2019-08-30
Contents have been reproduced by permission of the publishers.
导出
全部期刊列表>>
微生物研究
亚洲大洋洲地球科学
NPJ欢迎投稿
自然科研论文编辑
ERIS期刊投稿
欢迎阅读创刊号
自然职场,为您触达千万科研人才
spring&清华大学出版社
城市可持续发展前沿研究专辑
Springer 纳米技术权威期刊征稿
全球视野覆盖
施普林格·自然新
chemistry
物理学研究前沿热点精选期刊推荐
自然职位线上招聘会
欢迎报名注册2020量子在线大会
化学领域亟待解决的问题
材料学研究精选新
GIANT
ACS ES&T Engineering
ACS ES&T Water
屿渡论文,编辑服务
阿拉丁试剂right
上海中医药大学
清华大学
复旦大学
南科大
北京理工大学
上海交通大学
隐藏1h前已浏览文章
课题组网站
新版X-MOL期刊搜索和高级搜索功能介绍
ACS材料视界
清华大学-1
武汉大学
浙江大学
天合科研
x-mol收录
试剂库存
down
wechat
bug