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Income modeling with the Weibull mixtures Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200731
Shaiful Anuar Abu Bakar; Dharini PathmanathanIn this paper, we introduce six Weibull based mixture distributions to model income data. Several statistical properties of these models are derived and their closed forms are presented. The mixture model parameters are estimated using the maximum likelihood method and their performances are assessed with respect to average income per tax unit data for ten countries using information based criteria

Simultaneous confidence band for the difference of regression functions of two samples Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200731
Jiakun Jiang; Li Cai; Lijian YangThis paper concerns the comparison of two sample non parametric regression. An asymptotically correct simultaneous confidence band (SCB) is proposed for the difference of twosample non parametric regression functions to achieve the goal of comparison. Simulation experiments provide strong evidence that corroborates the asymptotic theory. The proposed SCB is used to analyze different samples of strata

Holt–Winters model with grey generating operator and its application Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200731
Lianyi Liu; Lifeng WuExponential smoothing is one of the most commonly used prediction methods. When the data has obvious periodicity and seasonality, Holt–Winters usually has a good prediction performance. However, the predicted results often do not meet our expectations when the trend of the original data is not clear. To further reduce the randomness of time series, a new method combining grey generating operator with

A class of claim distributions: Properties, characterizations and applications to insurance claim data Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200731
Zubair Ahmad; Eisa Mahmoudi; Gholamhossien HamedaniActuaries are often in search of finding an adequate model for actuarial and financial risk management problems. In the present work, we introduce a class of claim distributions useful in a number of lifetime analyses. A special submodel of the proposed family, called the Weibull claim model, is considered in detail. Some mathematical properties along with certain characterizations are derived and

An improved general class of estimators for finite population mean in simple random sampling Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200730
Javid Shabbir; Sat Gupta; Saadia MasoodRecently Pal et al. introduced a mean estimator which generalized most of the known mean estimators. We introduce a class of estimators that performs better than Pal et al. estimator. Expressions for bias and MSE for the proposed estimator are derived up to first order of approximation. We use the six datasets for numerical comparison.

Pliable lasso for the multinomial logistic regression Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200729
Theophilus Quachie Asenso; Hai Zhang; Yong LiangIn this paper, we study the multinomial logistic regression with interactive effects. Our approach involves the implementation of the pliable lasso penalty which allows for estimating the main effects of the covariates X and an interaction effects between the covariates and a set modifiers Z. The hierarchical penalty helps to avoid overfitting by excluding the interaction effects when the corresponding

Test for high dimensional regression coefficients of partially linear models Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200630
Siyang Wang; Hengjian CuiPartially linear models attract much attention to investigate the association between predictors and the response variable when the dependency on some predictors may be nonlinear. However, the hypothesis test for significance of predictors is still challenging, especially when the number of predictors is larger than sample size. In this paper, we reconsider the test procedure of Zhong and Chen (2011

Variance reduction approach for the volatility over a finitetime horizon Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200725
Yuping Song; Zheng Sun; Qicheng Zhao; Youyou ChenThe volatility is a measure for the uncertainty of an asset’s return and is used to reflect the risk level of a financial asset. In this article, we consider the double kernel nonparametric estimator for the volatility function in a diffusion model over a finitetime span based on high frequency sampling data. Under the minimum conditions, the asymptotic mixed normality for the underlying estimator

Optimum stratification for a generalized auxiliary variable proportional allocation under a superpopulation model Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200725
Bhuwaneshwar Kumar Gupt; Md. Irphan AhamedUnder a heteroscedastic regression superpopulation (HRS) model considered by Rao, Gupt obtained several modelbased allocations including two generalized allocations, one of which is generalized auxiliary variable proportional allocation (GAVPA). In this article, we investigate the problem of optimum stratification for GAVPA under the HRS model. Equations giving optimum points of stratification (OPS)

Asymptotics in a probit model for directed networks Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200722
Qian Wang; Qiuping Wang; Jing LuoIn this paper, we use the probit distribution to model the degree heterogeneity of the directed networks. We refer this model as the Probit Network Model, in which each edge is independently distributed as a Bernoulli random variable with a success probability measured by the probit function with a set of degree parameters. By using the moment equation to estimate the degree parameters, we establish

Generalized method of moment for casecohort under additive hazards model Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200722
Wenpeng ShangIn rare disease study, the failure rate is low in a large cohort of subjects due to constraint by funding and research time. Casecohort design is a widely used sampling scheme for costeffective study. The weighted pseudoscore (PS) estimators are proposed in the additive hazards model with data generated under casecohort design. In this article, we present two more effective estimators: the generalized

Higher order calibrated estimator in twostage sampling Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200722
Veronica I. Salinas; Stephen A. Sedory; Sarjinder SinghIn this paper, we consider a situation when the population variances of the auxiliary variable in the first stage units selected in a sample are known in addition to the known population means of the auxiliary variable. The higher order calibration weights which make use of both the population variances and population means at the estimation stage for both the first stage units and the second stage

Incorporating a changepoint estimator when bootstrapping the empirical distribution of a stationary process Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200722
B. Gail Ivanoff; Neville C. WeberThe moving block bootstrap can be used to determine critical values for test statistics used to detect a changepoint in the marginal distribution of a stationary time series. We examine the impact of incorporating an estimator of the changepoint when centering the bootstrap blocks and establish conditions under which the bootstrapped test statistics remain stochastically bounded regardless of whether

The parametric and additive partial linear regressions based on the generalized odd loglogistic lognormal distribution Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200721
Julio C. S. Vasconcelos; Gauss M. Cordeiro; Edwin M. M. Ortega; Marco A. M. BiaggioniWe propose two new regressions based on the generalized odd loglogistic lognormal distribution allowing for positive and negative skewness to model bimodal data. The first one is the parametric regression and the second one is an additive partial linear regression. The new regressions aim to estimate the linear and nonlinear effects of covariables on the response variable and generalize some existing

On improved class of difference type estimators for population median in survey sampling Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200721
Javid Shabbir; Sat Gupta; Ghulam NarjisWe propose two new improved class of difference type estimators for population median under simple random sampling (SRS) and twophase sampling (TPS). Expressions for bias and MSE are derived up to first order of approximation. We make a comparison of proposed estimators with all other commonly known estimators in literature. Numerical findings show that the proposed class of estimators perform better

Nonparametric smoothed quantile difference estimation for lengthbiased and rightcensored data Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200720
Jianhua Shi; Yutao Liu; Jinfeng XuWe consider the nonparametric analysis of lengthbiased and rightcensored data (LBRC) by quantile difference. With its desirable properties such as superior robustness and easy interpretation, quantile difference has been widely used in practice, in particular, for missing and survival data. Existing approaches for nonparametric estimation of quantile difference in lengthbiased survival data, however

Weighted stepdown confidence procedures with applications to gene expression data Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200720
Yang Yu; John T. Chen; Arthur B. YehIt is critical to incorporate additional information of parameters into the simultaneous estimation process. In this paper, we propose a new confidence method that utilizes the information on parameter priority and keeps the elegance and simplicity of Holm’s weighted testing procedure. The new method is grounded on the method of random partitions, in conjunction with probability inequalities, to ensure

Economic and economicstatistical designs of variable sample size and sampling interval coefficient of variation chart Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200720
YiYing Chew; Michael B. C. Khoo; Khai Wah Khaw; Wai Chung YeongIn the literature, the variable sample size and sampling interval (VSSI) coefficient of variation (CV) chart was shown to have a better statistical performance than the Shewhart (SH) CV chart which uses fixed sample size and sampling interval. The VSSI CV chart adopts more frequent sampling and larger sample size when the process quality deteriorates for quicker detection of a process shift as there

Log transformations: What not to expect when you’re expecting Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200720
William C. Bridges; Neil J. Calkin; Catherine M. Kenyon; Matthew J. SaltzmanWe note that log transformations can be problematic when the variance of the underlying distribution is other than very small. We illustrate these problems in terms of lognormal sampling issues, interval estimation of the mean, and comparison of lognormal and logbinomial distributions with similar means and variances.

Modeling atmospheric dispersion: Uncertainty management of release height after a nuclear accident Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200717
A. S. GargoumAtmospheric dispersion is a process that involves many uncertainties in model parameters, inputs and source parameters. In this article, we present an uncertainty management procedure for the height release at source which is a key parameter in modeling the subsequent dispersal of contamination after a nuclear accident. When setting the initial parameters of a dispersal model, it is difficult to estimate

Assessment of local influence in spatial elliptical linear measurement error models Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200716
Hadi Emami; Ali M. MosammamIn this paper, we consider estimation and inference procedures in spatial linear models when some of the covariates are measured with errors. It is assumed that the additive error distributed according to the law belonging to the class of elliptically contoured distributions. The development of the corrected score function with the family of elliptical distributions is the basis for derivation of the

Numerical pricing of exchange option with stock liquidity under Bayesian statistical method Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200715
Rui Gao; Yaqiong Li; Yanfei BaiIn the paper, we consider the pricing problem of exchange option where the two underlying stocks are correlated and imperfectly liquid. Firstly, we obtain an explicit pricing formula for the exchange option in the incomplete market by Esscher measure transformation. Then, a Bayesian statistical method is proposed to estimate the unknown parameters, since the parameter calibration of exchange option

Twosample test based on empirical likelihood ratio under semicompeting risks data Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200715
JinJian Hsieh; JyunPeng LiThis article considers the twosample testing problem of the survival function of the non terminal event time under semicompeting risks data. The empirical likelihood function is constructed for the survival function estimation of the non terminal event time, then maximize it by the PSO (Particle swarm optimization) algorithm to obtain the MLE. For the testing problem, the article develops the empirical

On stochastic comparisons of coherent systems with two different types of components Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200715
Maryam KelkinnamaThis paper is a study on comparison between coherent systems with independent and heterogeneous components. Specifically, we consider 3component coherent systems composed of two different types of components where we assume that component lifetimes follow the wellknown proportional hazards model. We stochastically compare such systems under different situations and based on some assumptions on the

Complete convergence theorem for negatively dependent random variables under sublinear expectations Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200714
Binxia Chen; Qunying WuUnder the condition that the Choquet integral exists, we study the complete convergence theorem for negatively dependent random variables under sublinear expectation space. Two general complete convergence theorems under sublinear expectation space are obtained, where the coefficient of weighted sum is the general function. This paper not only extends the complete convergence theorem in the traditional

The queue G e o X / G / 1 / N + 1 revisited Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200714
Veena Goswami; M. L. ChaudhryWe present analytic expressions (in terms of roots of the underlying characteristic equation) for the steadystate distributions of the number of customers for the finitestate queueing model G e o X / G / 1 / N + 1 with partialbatch rejection policy. We obtain the systemlength distributions at a servicecompletion epoch by applying the imbedded Markov chain technique. Using the roots of the related

New shrinkage parameters for the inverse Gaussian Liu regression Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200714
Khalid Naveed; Muhammad Amin; Saima Afzal; Muhammad QasimIn the Inverse Gaussian Regression (IGR), there is a significant increase in the variance of the commonly used Maximum Likelihood (ML) estimator in the presence of multicollinearity. Alternatively, we suggested the Liu Estimator (LE) for the IGR that is the generalization of Liu. In addition, some estimation methods are proposed to estimate the optimal value of the Liu shrinkage parameter, d. We investigate

Confidence distributions and empirical Bayes posterior distributions unified as distributions of evidential support Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200710
David R. BickelWhile empirical Bayes methods thrive in the presence of the thousands of simultaneous hypothesis tests in genomics and other largescale applications, significance tests and confidence intervals are considered more appropriate for small numbers of tested hypotheses. Indeed, for fewer hypotheses, there is more uncertainty in empirical Bayes estimates of the prior distribution. Confidence intervals have

New results on stochastic comparisons of finite mixtures for some families of distributions Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200709
Hossein Nadeb; Hamzeh TorabiThe classical finite mixture model is an effective tool to describe the lifetimes of the items existing in a random sample which are selected from some heterogeneous populations. This paper carries out stochastic comparisons between two classical finite mixture models in the sense of the usual stochastic order, when the subpopulations follow a wide class of distributions including the scale model,

Robust tests of the equality of two highdimensional covariance matrices Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200707
Xuemin Zi; Hui ChenIt is of great importance in both theory and application to test the equality of two covariance matrices Σ1 and Σ2. This article proposes a new robust test based on spatial sign statistic regarding H0:Σ1=Σ2 in highdimensional setting, and shows that the test statistic is asymptotically normal under elliptical distribution. Besides theoretical properties, simulation results also show that the new test

Strong laws of large numbers for WAPND Banachvalued random elements Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200707
Mehdi Jafari; Hamid Reza Nili Sani; Abolghasem BozorgniaIn this article, we first prove Borel–Cantelli lemma and some strong laws of large numbers for APND random variables. Then, we introduce a new class of dependent random elements, called briefly WAPND, taking values in a separable Banach space. For this new class, we extend some strong laws of large numbers.

Computational analysis and optimization of randomized control of Npolicy for an M/G/1/K queue with starting failures Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200707
DongYuh YangThis article aims to present the steadystate analysis in finitebuffer M/G/1 queues with starting failures under a randomized control of Npolicy. When the system empties, the server is turned off. If the system size reaches the threshold N, the server is turned on with probability p or turned off with probability 1−p. The server needs a startup time before providing service. If the server is started

Hybrid differential evolutionary strawberry algorithm for realparameter optimization problems Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200707
Wali Khan Mashwani; Abdullah Khan; Atila Göktaş; Yuksel Akay Unvan; Ozgur Yaniay; Abdelouahed HamdiEvolutionary algorithms (EAs) is a family of populationbased nature optimization methods. In contrast to classical optimization techniques, EAs provide a set of approximated solutions for different test suites of optimization and realworld problems in single simulation. In the last few years, hybrid EAs have received much attention by utilizing the valuable aspects of different nature of search strategies

Preface Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200607
Xufeng Zhao; Jingyuan Shen(2020). Preface. Communications in Statistics  Theory and Methods: Vol. 49, Third International Symposium on Stochastic Models in Reliability Engineering, Life Sciences and Operations Management, pp. 35853588.

Optimization problems for consecutive2outofn:G system Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200602
Lei Zhou; Hisashi Yamamoto; Taishin Nakamura; Xiao XiaoThis paper considers the optimization problems for a consecutive2outofn:G system where n is considered to be fixed or random. When the number of components is constant, the optimal number of components and the optimal replacement time are discussed by minimizing the expected cost rates. Furthermore, we focus on the above discussions again when n is a random variable. We give an approximate value

Improved strategy to collect sensitive data by using negative binomial and negative hypergeometric distribution as randomization devices Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200707
Niharika Yennum; Stephen A. Sedory; Sarjinder SinghIn this paper, we improve upon the negative binomial randomized response model by implementing a twostage randomization process. Using the modified estimator of the proportion of members of a population possessing a sensitive attribute, we claim to achieve both better efficiency and better protection. The findings are verified based on extensive simulation study. Then we improvise the technique of

Reliability and sensitivity analysis of a repairable koutofn:G system with two failure modes and retrial feature Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200707
Linmin Hu; Sijia Liu; Rui Peng; Zhaocai LiuThis paper investigates the reliability and sensitivity analysis for a repairable koutofn:G system with retrial of failed components. Such a model has important practical applications in fully automatic systems, and the most typical one is fully automatic manufacturing system. Markov models for availability and reliability of the system whose components are all subject to two failure modes are presented

In defense of LASSO Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200707
Chi Tim Ng; Woojoo Lee; Youngjo LeeAlthough LASSO has been criticized for selecting too many covariates, it is illustrated in this paper that the bigger model chosen by LASSO method is suitable for exploratory research aiming at identifying all potential causes for further scientific investigation. Up to now, all criticisms assume that the covariates are observed without measurement errors, which is not likely to be true in many practical

Welch’s ANOVA: Heteroskedastic skewt error terms Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200706
N. CelikIn analysis of variance (ANOVA) models, it is generally assumed that the distribution of the error terms is normal with mean zero and constant variance σ2. Traditionally, a least square (LS) method is used for estimating the unknown parameters and testing the null hypothesis. It is known that, when the normality assumption is not satisfied, LS estimators of the parameters and the test statistics based

Local asymptotic normality for a periodically time varying long memory parameter Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200706
Amine Amimour; Karima BelaideA periodically time varying long memory parameter version of the fixed long memory parameter case local asymptotic normality (LAN) results are implemented here. The process is assumed to be invertible and causal for simplicity. We prove that the general condition of LAN is verified by our model. The simulation experiment is carried out for studying the distribution of the central sequence in LAN property

Statistical inference of TypeI progressively censored stepstress accelerated life test with dependent competing risks Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200704
Xuchao Bai; Yimin Shi; Hon Keung Tony NgThis paper considers a stepstress accelerated dependent competing risks model under progressively TypeI censoring schemes. The dependence structure between competing risks is modeled by a general bivariate function, the cumulative exposure model is assumed and the accelerated model is described by the power rule model. The point and interval estimation of the model parameters and the reliability

Maintenance strategy of multicomponent system based on structure updating and group importance measure Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200702
Yijie Chen; Hailin FengFor a multicomponent system, a maintenance strategy based on system structure updating and group importance measure is proposed. First, a system structure is determined by redefining its component grades, furthermore, the system structure updating is realized by introducing its survival signature. And based on the current system structure, a corrective maintenance that combines sequentially minimal

Complete and complete integral convergence for arrays of row wise widely negative dependent random variables under the sublinear expectations Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200702
Dawei Lu; Yao MengIn this article, complete and complete integral convergence theorems are obtained for arrays of row wise widely negative dependent random variables under the sublinear expectations. We improve the results by (Lin and Feng 2019 Lin, Y. W., and X. W. Feng. 2019. Complete convergence and strong law of large numbers for arrays of random variables under sublinear expectations. Communications in Statistics:

Firstpassage problems for diffusion processes with statedependent jumps Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200702
Mario LefebvreLet X(t) be a timehomogeneous jumpdiffusion process. We assume that the jump size depends on the value of X(t). We obtain analytical results for the moments of T(x) and of X(T(x)), where T(x) is the first time that the process leaves the interval (a, b). We also compute P[X(T(x))≤a]. These results have applications in financial mathematics.

Quantile regression for massive data with networkinduced dependence, and application to the New York statewide planning and research cooperative system Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200701
Yanqiao Zheng; Xiaobing Zhao; Xiaoqi ZhangMedical costs are often skewed to the right, heteroscedastic, and having a sophisticated relation with covariates. Moreover, medical cost datasets are always massive, such as in the New York Statewide Planning and Research Cooperative System Expenditure Study. Different observations can depend on each other as the spatial distribution of diseases induces complex correlation among patients coming from

A new extension of the FGM copula with an application in reliability Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200701
Rasha Ebaid; Walid Elbadawy; Essam Ahmed; Abdalla AbdelghalyWe propose a new symmetric extension of the bivariate FarlieGumbelMorgenstern (FGM) copula with given marginals. The main feature of this new extension is the higher dependence level it permits between random variables. It is shown that the range of Spearman’s Rho is [−.33, 1]. We use this new extension to estimate reliability in a dependent stressstrength model with an application to the Egyptian

Optimal design of onesided exponential EWMA charts based on median run length and expected median run length Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200630
YuLong Qiao; JinSheng Sun; Philippe Castagliola; XueLong HuExponential type charts are useful tools to monitor the time between events in highquality processes with a low defect rate. Most studies on exponential charts are designed with the average run length (ARL) metric. The only use of ARL in the design of control charts is sometimes criticized because the shape of the run length (RL) distribution of control charts changes with the shift size. In fact

Test for high dimensional regression coefficients of partially linear models Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200630
Siyang Wang; Hengjian CuiPartially linear models attract much attention to investigate the association between predictors and the response variable when the dependency on some predictors may be nonlinear. However, the hypothesis test for significance of predictors is still challenging, especially when the number of predictors is larger than sample size. In this paper, we reconsider the test procedure of Zhong and Chen (2011

The mean, variance, and bias of the OLS based estimator of the extremum of a quadratic regression model for small samples Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200625
Andreas Karlsson RosenbladAbstract Many economic theories suggest that the relation between two variables y and x follow a function forming a convex or concave curve. In the classical linear model (CLM) framework, this function is usually modeled using a quadratic regression model, with the interest being to find the extremum value or turning point of this function. In the CLM framework, this point is estimated from the ratio

Penalized Cox regression with a fiveparameter spline model Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200625
JiaHan Shih; Takeshi EmuraHazard models with cubic spline functions have a number of advantages to the existing regression models. For analysis of rightcensored data, we introduce a penalized Cox regression method using five Mspline basis functions. The proposed spline model is more flexible than the existing parametric models as it produces the increasing, decreasing, convex, concave, and constant hazard functions. To illustrate

Highdimensional asymptotic results for EPMCs of W and Z rules Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200622
Takayuki Yamada; Tetsuro Sakurai; Yasunori FujikoshiThis paper is concerned with highdimensional asymptotic results for W and Z rules when the sample size N and the dimension are large. Firstly, we give a unified location and scale mixture expression of the standard normal distribution for W and Z statistics. Then, the EPMCs (Expected Probability of Misclassifications) of W and Z rules are obtained in expanded forms with errors of O(N−2). It is

Large deviations for empirical measures of generalized random graphs Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200618
Qun Liu; Zhishan DongIn a generalized random graph with random vertex weights, we investigate the asymptotic behaviors for two crucial empirical measures: The empirical pair measure, which represents the number of edges connecting each pair of weights, and the empirical neighborhood measure, which interprets the number of vertices of a given weight connected to a given number of vertices of each weight. By some mixing

Empirical likelihood for panel data models with spatial errors Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200618
Yinghua Li; Yuan Li; Yongsong QinFor panel data models with spatial errors, the empirical likelihood ratio statistics are constructed for the parameters of the models. It is shown that the limiting distributions of the empirical likelihood ratio statistics are chisquared distributions, which are used to construct confidence regions for the parameters of the models. A simulation study is conducted to show the performance of the proposed

Nonmarginal feature screening for additive hazard model with ultrahighdimensional covariates Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200617
Zili Liu; Zikang XiongSurvival data with ultrahighdimensional covariates have been frequently encountered in medical studies and other fields. In this article, we propose a nonmarginal feature screening procedure for the additive hazard model with ultrahighdimensional covariates. The proposed method utilizes the joint effects between covariates, which can effectively identify active covariates that are jointly dependent

Confidencecredible intervals Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200617
Ivair R. Silva; Dionatan W. R. OliveiraFrequentist and Bayesian approaches for interval estimation usually produce conflicting results if applied to analyze the same data set. Paradoxically, there is no unanimity in the literature on whether frequentist and Bayesian approaches are indeed concurrent theories. Thus, a fundamental question arises: frequentist and Bayesian approaches for interval estimation could be somehow reconciled? This

Localized mixture models for prediction with application Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200617
Najla M. QarmalahThis paper explores how localized mixture models can be used for prediction using time series data. The estimation method presented in this study is a kernelweighted version of an EMalgorithm, where exponential kernels with different bandwidths are used as weight functions. Nadaraya–Watson and local linear estimators are used to carry out localized estimations. Furthermore, in order to demonstrate

Estimation and inference for mixture of partially linear additive models Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200617
Yi Zhang; Weiquan PanIn this paper, a semiparametric mixture of regression models is proposed, where the regression functions are partially linear additive while the mixing proportions and variances are unknown constant. The asymptotic normality of the SBK estimators and the model selection consistency of the proposed BIC based on Bspline estimators are established. Simulations and applications are presented to illustrate

Inactivity stochastic precedence order Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200616
Amit Kumar Misra; Vaishali Gupta; Ruby ChanchalThe aim of this article is to extend the inactivity probability order, defined by Abouelmagd et al. (Communications in StatisticsTheory and Methods 47, 3293–3304, 2018), to the case of non independent random variables. It is done by defining a new stochastic order based on the inactivity times of two non negative dependent random variables and the stochastic precedence order. Some characterizations

Construction and existence of constant block sum PBIB designs Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200616
Namisha Bansal; Davinder Kumar GargThe present article proposes three series of partially balanced incomplete constant block sum designs constructed using regular graphs. Two series develop a threeassociate class PBIB designs and one develops a fiveassociate class PBIB design. Moreover, we were able to show the existence of constant block sum PBIB designs with their parameters for a specified association scheme. Towards the end, we

Construction of optimal supersaturated designs via generalized Hadamard matrices Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200615
Min Li; MinQian Liu; Fasheng Sun; Dong ZhangA supersaturated design (SSD) is a factorial design whose run size is not enough for estimating all the main effects. Such designs have received much recent interest because of their potential in factor screening experiments. This paper first shows that the design obtained by the Kronecker sum of a balanced design and a generalized Hadamard matrix (i.e., a matrix with both itself and its transpose