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  • Bayesian multi-way balanced nested MANOVA models with random effects and a large number of the main factor levels
    Metrika (IF 0.679) Pub Date : 2020-10-11
    Chun-Lung Su

    This article considers the balanced nested multi-way multivariate analysis of variance (MANOVA) models with random effects and a large number of main factor levels under certain prior assumptions. Two different parametrizations for the MANOVA models with random effects and the corresponding explicit asymptotics are established. The asymptotic approximations are then compared with those obtained from

    更新日期:2020-10-11
  • Additive functional regression in reproducing kernel Hilbert spaces under smoothness condition
    Metrika (IF 0.679) Pub Date : 2020-10-09
    Yuzhu Tian, Hongmei Lin, Heng Lian, Zengyan Fan

    Additive functional model is one popular semiparametric approach for regression with a functional predictor. Optimal prediction error rate has been demonstrated in the framework of reproducing kernel Hilbert spaces (RKHS), which only depends on the property of the RKHS but not on the smoothness of the function. We extend this previous theoretical result by establishing faster convergence rates under

    更新日期:2020-10-11
  • New efficient spline estimation for varying-coefficient models with two-step knot number selection
    Metrika (IF 0.679) Pub Date : 2020-10-03
    Jun Jin, Tiefeng Ma, Jiajia Dai

    One of the advantages for the varying-coefficient model is to allow the coefficients to vary as smooth functions of other variables and the coefficients functions can be estimated easily through a simple B-spline approximations method. This leads to a simple one-step estimation procedure. We show that such a one-step method cannot be optimal when some coefficient functions possess different degrees

    更新日期:2020-10-04
  • A new test of multivariate normality by a double estimation in a characterizing PDE
    Metrika (IF 0.679) Pub Date : 2020-08-31
    Philip Dörr, Bruno Ebner, Norbert Henze

    This paper deals with testing for nondegenerate normality of a d-variate random vector X based on a random sample \(X_1,\ldots ,X_n\) of X. The rationale of the test is that the characteristic function \(\psi (t) = \exp (-\Vert t\Vert ^2/2)\) of the standard normal distribution in \({\mathbb {R}}^d\) is the only solution of the partial differential equation \(\varDelta f(t) = (\Vert t\Vert ^2-d)f(t)\)

    更新日期:2020-08-31
  • Uniform augmented q -level designs
    Metrika (IF 0.679) Pub Date : 2020-08-28
    Zongyi Hu, Jiaqi Liu, Yi Li, Hongyi Li

    In many practical applications, follow-up experimental designs are commonly used to explore the relationship between inputs and outputs steps by steps. As some additional resources could be available to the experimenter after the first step, some additional runs or factors may be added in the follow-up stage. The issue of uniform augmented q-level designs is investigated in this paper. Using the level

    更新日期:2020-08-28
  • Estimation of autocovariance matrices for high dimensional linear processes
    Metrika (IF 0.679) Pub Date : 2020-08-26
    Konrad Furmańczyk

    In this paper under some mild restrictions upper bounds on the rate of convergence for estimators of \(p\times p\) autocovariance and precision matrices for high dimensional linear processes are given. We show that these estimators are consistent in the operator norm in the sub-Gaussian case when \(p={\mathcal {O}}\left( n^{\gamma /2}\right) \) for some \(\gamma >1\), and in the general case when \(

    更新日期:2020-08-27
  • A new method of finding component orthogonal arrays for order-of-addition experiments
    Metrika (IF 0.679) Pub Date : 2020-08-19
    Yuna Zhao, Zhiwei Li, Shengli Zhao

    The order-of-addition experiments aim at determining the optimal order of m components such that the yields are optimized. The component orthogonal array (COA) allows to economically find out the optimal order by testing some carefully selected orders from all of the m! orders. This paper proposes a new method of finding COAs of broader run sizes. As an application of the new method, some COAs with

    更新日期:2020-08-19
  • On histogram-based regression and classification with incomplete data
    Metrika (IF 0.679) Pub Date : 2020-08-19
    Eric Han, Majid Mojirsheibani

    We consider the problem of nonparametric regression with possibly incomplete covariate vectors. The proposed estimators, which are based on histogram methods, are fully nonparametric and straightforward to implement. The presence of incomplete covariates is handled by an inverse weighting method, where the weights are estimates of the conditional probabilities of having incomplete covariate vectors

    更新日期:2020-08-19
  • On past geometric vitality function of order statistics
    Metrika (IF 0.679) Pub Date : 2020-08-18
    Ramanathan Gayathri, Enchakudiyil Ibrahim Abdul Sathar

    In this article, we propose geometric vitality function introduced by Nair and Rajesh (IAPQR Trans 25(1):1–8, 2000) for the past lifetime of a random variable. This measure plays a vital role in analysing different characteristics of a system/component when it fails in the interval (0, t). The monotonic behaviour and some ordering properties in terms of the proposed measure were studied under certain

    更新日期:2020-08-19
  • Construction of mixed-level supersaturated split-plot designs
    Metrika (IF 0.679) Pub Date : 2020-08-17
    K. Chatterjee, C. Koukouvinos

    This paper considers the construction of mixed-level supersaturated split-plot designs (SSSPDs) which are very useful in screening situations where the number of factors is larger than the number of available observations and several of these factors have levels that they are hard to change. As a benchmark of obtaining optimal SSSPDs, lower bounds to our proposed designs are established. Illustrative

    更新日期:2020-08-18
  • General flation models for count data
    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
  • Maximin distance designs based on densest packings
    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
  • On the properties of hermite series based distribution function estimators
    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
  • Least squares moment identification of binary regression mixture models
    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
  • Asymptotic properties of mildly explosive processes with locally stationary disturbance
    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
  • Parallel inference for big data with the group Bayesian method
    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
  • On the ARCH model with stationary liquidity
    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
  • Random discretization of stationary continuous time processes
    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
  • A shrinkage approach to joint estimation of multiple covariance matrices
    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
  • Efficient Estimation for Varying-Coefficient Mixed Effects Models with Functional Response Data
    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
  • Statistical inference based on a new weighted likelihood approach
    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
  • An empirical likelihood method for quantile regression models with censored data
    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
  • Efficient crossover designs for non-regular settings
    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
  • On the equivalence between the LRT and F-test for testing variance components in a class of linear mixed models
    Metrika (IF 0.679) Pub Date : 2020-05-28
    Fares Qeadan, Ronald Christensen

    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
  • Conditional maximum Lq-likelihood estimation for regression model with autoregressive error terms
    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
  • A general multivariate new better than used (MNBU) distribution and its properties
    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
  • Variable selection for sparse logistic regression
    Metrika (IF 0.679) Pub Date : 2020-02-06
    Zanhua Yin

    We consider the variable selection problem in a sparse logistical regression model. Inspired by the square-root Lasso, we develop a weighted score Lasso for logistical regression. The new method yields the estimation \({\ell }_1\) error bound under similar assumptions as introduced in Bach et al. (Electron J Stat 4:384–414, 2010). Compared to standard Lasso, the weighted score Lasso provides a direct

    更新日期:2020-02-06
  • Maximum product of spacings prediction of future record values
    Metrika (IF 0.679) Pub Date : 2020-02-06
    Grigoriy Volovskiy, Udo Kamps

    A spacings-based prediction method for future upper record values is proposed as an alternative to maximum likelihood prediction. For an underlying family of distributions with continuous cumulative distribution functions, the general form of the predictor as a function of the estimator of the distributional parameters is established. A connection between this method and the maximum observed likelihood

    更新日期:2020-02-06
  • North-east bivariate records
    Metrika (IF 0.679) Pub Date : 2020-02-03
    N. Balakrishnan, A. Stepanov, V. B. Nevzorov

    Bivariate records have many application in different fields such as hydrology, economy, finance and weather forecasting; see, for example, the works of Bayramoglu (Metrika 79:725–747, 2016) and Kemalbay and Bayramoglu (Turk J Math 43:1474–1491, 2019). It should be noted that there are various definitions of bivariate records. In this paper, we discuss the concept of north-east bivariate records, originally

    更新日期:2020-02-03
  • Robust composite weighted quantile screening for ultrahigh dimensional discriminant analysis
    Metrika (IF 0.679) Pub Date : 2020-01-06
    Fengli Song, Peng Lai, Baohua Shen

    This paper is concerned with feature screening for the ultrahigh dimensional discriminant analysis. A new feature screening procedure based on the conditional quantile is proposed. The proposed procedure has some desirable features. First, it is model-free which does not require specific discriminant model and can be directly applied to the multi-categories situation. Second, it is robust against heavy-tailed

    更新日期:2020-01-06
  • A unified approach to constructing correlation coefficients between random variables
    Metrika (IF 0.679) Pub Date : 2020-01-01
    Majid Asadi, Somayeh Zarezadeh

    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
  • Convergence rate of kernel regression estimation for time series data when both response and covariate are functional
    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
  • Estimation of finite mixture models of skew-symmetric circular distributions
    Metrika (IF 0.679) Pub Date : 2019-12-09
    Yoichi Miyata, Takayuki Shiohama, Toshihiro Abe

    Analysis of circular data is challenging, since the usual statistical methods are unsuitable and it is necessary to use circular periodic probabilistic models. Because some actual circular datasets exhibit asymmetry and/or multimodality, finite mixtures of symmetric circular distributions to model and fit these data have been investigated. However, it is necessary to question the predominant assumption

    更新日期:2019-12-09
  • Asymmetrical split-plot designs with clear effects
    Metrika (IF 0.679) Pub Date : 2019-12-04
    Xiaoxue Han, Jianbin Chen, Min-Qian Liu, Shengli Zhao

    The fractional factorial split-plot (FFSP) design is an important experimental design both in theory and in practice. There is extensive literature on the two-level FFSP design and its various variants. However, there is little work on the s-level FFSP design and its variants in the asymmetrical (i.e., mixed-level) case, where s is any prime or prime power. Such designs are commonly used e.g. in agriculture

    更新日期:2019-12-04
  • Increasing concave orderings of linear combinations of order statistics with applications to social welfare
    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
  • Ordering extremes of exponentiated location-scale models with dependent and heterogeneous random samples
    Metrika (IF 0.679) Pub Date : 2019-11-21
    Sangita Das, Suchandan Kayal

    This paper is devoted to some ordering results for the largest and the smallest order statistics arising from dependent heterogeneous exponentiated location-scale random observations. We assume that the sets of observations are sharing a common or different Archimedean copula(s). Sufficient conditions for which the usual stochastic order and the reversed hazard rate order between the extreme order

    更新日期:2019-11-21
  • Reliability of a coherent system equipped with two cold standby components
    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
  • Classes of Multiple Decision Functions Strongly Controlling FWER and FDR.
    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
  • Optimal Hypothesis Testing: From Semi to Fully Bayes Factors.
    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
  • Quadratic semiparametric Von Mises calculus.
    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
  • Integral transform methods in goodness-of-fit testing, I: the gamma distributions
    Metrika (IF 0.679) Pub Date : 2019-10-29
    Elena Hadjicosta, Donald Richards

    We apply the method of Hankel transforms to develop goodness-of-fit tests for gamma distributions with given shape parameters and unknown rate parameters. We derive the limiting null distribution of the test statistic as an integrated squared Gaussian process, obtain the corresponding covariance operator and oscillation properties of its eigenfunctions, show that the eigenvalues of the operator satisfy

    更新日期:2019-10-29
  • Consistency for the negative binomial regression with fixed covariate
    Metrika (IF 0.679) Pub Date : 2019-10-24
    Rafael Weißbach, Lucas Radloff

    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
  • Discriminant analysis based on binary time series
    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
  • Inequalities for Gaussian random variables under Archimedean copula dependence
    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
  • Minimax estimation of a bivariate cumulative distribution function
    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
  • Locally D -optimal designs for heteroscedastic polynomial measurement error models
    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
  • Regularized quantile regression for ultrahigh-dimensional data with nonignorable missing responses
    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
  • Quadrupling: construction of uniform designs with large run sizes
    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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