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On negative cumulative extropy with applications Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201018
Saeid Tahmasebi; Abdolsaeed ToomajAbstract Recently, an alternative measure of uncertainty termed by extropy was proposed by Lad et al. Accordingly, a cumulative residual extropy is also introduced by replacing the survival function in place of the density function in the extropy. In this paper, we define negative cumulative extropy (NCEX) measure of information and study several properties of this concept. We then elaborate the NCEX

Valuation of mortgage passthrough securities with partial prepayment risk Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201016
Congjin Zhou; Guojing Wang; Liang Liu; Jie GuoAbstract We develop a valuation model for mortgage passthrough securities with partial prepayment risk using an intensitybased approach. For the single mortgage contract in a given pool of mortgage loans, the ratio of prepayment amount to outstanding principal at partial prepayment time is described by a stochastic process, and the occurrence time of prepayments is modeled by jump time of a Cox process

A note on the stochastic precedence order between component redundancy and system redundancy for koutofn systems Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201014
Mithu Rani Kuiti; Nil Kamal Hazra; Maxim FinkelsteinAbstract Stochastic precedence order is a natural type of comparison for random variables in numerous engineering applications (e.g., for the stressstrength modeling). In this note, we show that, for a koutofn system, redundancy at the component level is superior to that at the system level with respect to the stochastic precedence order. Cases of active and cold redundancy are considered. Similar

Analytic expressions for the positive definite and unimodal regions of GramCharlier series Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201014
Oh Kang KwonAbstract It often arises in practice that, although the first few moments of a distribution are known, the density of the distribution cannot be determined in closed form. In such cases, GramCharlier and Edgeworth series are commonly used to analytically approximate the unknown density in terms of the known moments. Although convenient, these series contain polynomial factors, and can hence lead to

A unified option pricing model with Markov regimeswitching double stochastic volatility, stochastic interest rate and jumps Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201014
Jianping Lyu; Yong Ma; Wei SunAbstract We consider a general option pricing framework incorporating the double Heston stochastic volatility, stochastic interest rate, jumps and Markov regime switching. Under the proposed framework, we derive the analytical pricing formulae for European options using Fourier transform technique. Numerical examples illustrate that the option prices and the implied volatility curves under different

Objective bayesian inference for quantile ratios in normal models Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201014
Sang Gil Kang; Woo Dong Lee; Yongku KimAbstract In medical research, it is important to compare quantiles of certain measures obtained from treatment and control groups, with the quantile ratio showing the effect of the treatment. In particular, inference of the quantile ratio based on large sample methods can be studied using a normal model. In this paper, we develop noninformative priors such as probability matching priors and reference

Statistical inference for component lifetime distribution from coherent system lifetimes under a proportional reversed hazard model Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201012
Adeleh Fallah; Akbar Asgharzadeh; Hon Keung Tony NgAbstract Proportional reversed hazard model and exponentiated distributions have received considerable attention in the statistical literature due to its flexibility. In this paper, we develop the tools for statistical inference of the lifetime distribution of components in a ncomponent coherent system while the system lifetimes are observed, the system structure is known and the component lifetime

Empirical likelihood based inference for varying coefficient panel data models with fixed effect Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201008
Wanbin Li; Liugen Xue; Peixin ZhaoAbstract In this paper, the empirical likelihoodbased inference is investigated with varying coefficient panel data models with fixed effect. A naive empirical likelihood ratio is firstly proposed after the fixed effect is corrected. The maximum empirical likelihood estimators for the coefficient functions are derived as well as their asymptotic properties. Wilk’s phenomenon of this naive empirical

Tail behavior and extremes of the betanormal distribution Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201008
Yingying Jiang; Baokun LiAbstract In this paper, the tail properties of the betanormal distribution and an asymptotic Millstype ratio are studied. Meanwhile, two applications are presented. The first application obtains the asymptotic behavior of the ratio of probability density functions and the ratio of the tails of the betanormal and Student’s t distributions. The other one considers the asymptotic distribution of the

Stochastic comparisons of parallel systems with generalized KumaraswamyG components Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201008
Suchandan Kayal; Phalguni NandaAbstract This paper treats the problem of stochastic comparisons of two parallel systems with independent heterogeneous components having lifetimes following exponentiated KumaraswamyG model. The cases of same and different parent distribution functions are considered. Majorization type partial ordersbased sufficient conditions in comparing the largest order statistics in terms of the usual stochastic

Confidence intervals with maximal average power Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201006
Christian Bartels; Johanna Mielke; Ekkehard GlimmAbstract We propose a frequentist testing procedure that maintains a defined coverage and is optimal in the sense that it gives maximal power to detect deviations from a null hypothesis when the alternative to the null hypothesis is sampled from a prespecified distribution (the prior distribution). Selecting a prior distribution allows to tune the decision rule. This leads to an increased power, if

On some counter examples of the bivariate and multivariate normal distributions: A brief survey Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201006
Indranil Ghosh; G.G. HamedaniAbstract We present some counterexamples of the classical and nonclassical bivariate and multivariate normal distributions to widen our knowledge of these distributions. We hope that this paper will provide practitioners and users of bivariate and multivariate normal distributions of better view on the necessary and sufficient conditions leading to bivariate and multivariate normal distributions regarding

Monitoring the process mean with an ATTRIVAR chart Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201006
Antonio Fernando Branco Costa; Antonio Faria NetoAbstract In this article, we propose an ATTRIVAR chart to control the process mean. With the ATTRIVAR chart, the sampling is performed in two stages, collecting attribute and variable sample data from the same sample (attribute plus variable data – ATTRIVAR). That is, if the first m items of the sample fail to pass the go gauge test, or they pass the nogo gauge test, the sampling moves on to stage

Bayesian prior information fusion for power law process via evidence theory Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201005
JunMing Hu; HongZhong Huang; YanFeng Li; HuiYing GaoAbstract The power law process (PLP) is widely used to analyze the failures of repairable systems, and the PLP parameter estimation is the primary concern for reliability assessment or maintenance decision making. Although the Bayesian estimation of the PLP has been studied in existing research, little attention has been paid to how to obtain its prior distribution, especially when the prior information

Bayesian inference in quantile functions Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201005
N. Unnikrishnan Nair; P. G. Sankaran; M. DileepkumarAbstract The role of quantile functions in modeling various forms of statistical data is well established. Generally classical procedures like method of moments, Lmoments, percentiles etc are employed in estimating the parameters of the model. In the present work an attempt is made to infer parameters in the Bayesian framework with special emphasis to distributions in which the quantile functions

Usual stochastic and reversed hazard orders of parallel systems with independent heterogeneous components Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201004
Ghobad Barmalzan; Sajad Kosari; Narayanaswamy BalakrishnanAbstract In this paper, we present some new ordering properties between two parallel systems comprising general independent heterogeneous components. More precisely, let X 1 , ⋯ , X n and Y 1 , ⋯ , Y n be independent nonnegative random variables with X i ∼ F ( x ; α i , β i ) and Y i ∼ F ( x ; θ i , λ i ) , i = 1 , ⋯ , n , where F ( . ) is an absolutely continuous distribution function with reversed

On a nonmonotonic ageing class based on the failure rate average Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20201004
Dhrubasish Bhattacharyya; Shyamal Ghosh; Murari MitraAbstract A nonmonotonic ageing class based on failure rate average has been introduced and its relationships with existing classes are explored. Closure properties under the basic reliability operations have been discussed and survival probability bounds as well as moment bounds have been derived. We also propose a nonparametric test to detect trend change in failure rate average assuming that proportion

Asymptotic properties of lower exponential spacings under TypeII progressive censoring Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200929
Alexandre Berred; Alexei StepanovAbstract In this paper, we discuss distributional and asymptotic properties of lower exponential spacings obtained from order statistics taken from progressive typeII censoring samples. We find conditions under which the sequence of logarithmic lower exponential spacings converges in probability and with probability one.

Jackknife empirical likelihood for the error variance in linear errorsinvariables models with missing data Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200929
HongXia Xu; GuoLiang Fan; JiangFeng WangAbstract Measurement errors and missing data are often arise in practice. Under this circumstance, we focus on using jackknife empirical likelihood (JEL) and adjust jackknife empirical likelihood (AJEL) methods to construct confidence intervals for the error variance in linear models. Based on residuals of the models, the biasedcorrected inverse probability weighted estimator of the error variance

Partial functional linear regression with autoregressive errors Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200928
Piaoxuan Xiao; Guochang WangAbstract In the presented paper, we introduce a partial functional linear model, where a scalar response variable is explained by a multivariate random variable and a functional random variable, and the relationship between the scalar response and both of the predictors is linear. Besides, the model has autoregressive errors. To estimate the model, we first expand the functional predictor and functional

On the almost sure limit theorem for the joint version of maxima and minima of nonstationary random fields Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200924
Zacarias Panga; Luísa PereiraWe obain an almost sure limit theorem for the joint version of maxima and minima of a nonstationary random field defined over discrete subsets of R 2 , under some dependence conditions.

Influential nodes and anomalous topic activities in social networks using multivariate time series and topic modeling Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200924
Suchismita GoswamiIt is important to understand the behavior within a social network, particularly excessive communications between nodes. Such excessive activities in a network provide an insight into the pattern of communication between nodes, which, in some cases, could lead to a fraudulent behavior. Scan statistics have been applied before to detect the excessive communications in email networks. However, they alone

Postselection inference of generalized linear models based on the lasso and the elastic net Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200924
Xiangyu Shi; Bo Liang; Qi ZhangPostselection inference has been an active research topic recently. A lot of work provided different ways to solve practical problems in many fields such as medicine, finance, and so on. In particular, postselection inference under the linear model is widely discussed. We extend it to generalized linear model and present new approaches for postselection inference for penalized least squares method

An estimation of a sensitive attribute using adjusted Kuk’s randomization device with stratified unequal probability sampling Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200921
GiSung Lee; ChangKyoon SonIn this article, we develop the estimation of the sensitive attribute proportion of the population which is composed of several clusters by applying unequal probability sampling to the Su et al.’s model which is an adjusted Kuk’s model. We estimate the sensitive parameter, its variance and variance estimator for each unequal probability sampling and twostage equal probability sampling. We extend our

Correction to: Aljarrah, M.A., Famoye, F. and Lee, C. (2015). A New WeibullPareto distribution. Communications in Statistics  Theory and Methods, 44:19, 40774095 Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200921
Reza Azimi; Mahdy EsmailianAljarrah et al. (2015) [A New WeibullPareto Distribution. Communications in Statistics  Theory and Methods, 44:19, 40774095] introduced and studied a new WeibullPareto distribution based on the quantile of loglogistic distribution.They used the method of maximum likelihood to estimate the parameters of the WeibullPareto distribution. But they made some mistakes in presenting the loglikelihood

Some results on the construction of sliced orthogonal arrays of parallelflats type Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200918
ShinFu TsaiSliced orthogonal arrays are useful combinatorial tools that can be used to construct sliced spacefilling designs for planning computer experiments with both quantitative and qualitative input variables. A new class of sliced orthogonal arrays called the sliced orthogonal arrays of parallelflats type is proposed in this paper to address this practical issue. Specifically, a set of sufficient and

Equilibrium dividend strategies for spectrally negative Lévy processes with time value of ruin and random time horizon Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200917
Yongxia Zhao; Hua Dong; Wei ZhongIn the spectrally negative Lévy risk model, we investigate the absolutely continuous dividend problem with a general discount function, which results in a timeinconsistent control problem. Under the assumptions of a time value of ruin and an exponential time horizon, we study the equilibrium dividend strategies within a game theoretic framework for the return function composed by the discount expected

Some new results on likelihood ratio ordering and aging properties of generalized order statistics Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200917
Maryam EsnaAshari; Mahdi Alimohammadi; Erhard CramerIn this article, we first study the likelihood ratio ordering of generalized order statistics (GOS) in both onesample and twosample problems. Then, we establish the transmission of the increasing hazard rate and decreasing reversed hazard rate aging properties of GOS. To do this, we extend Karlin’s basic composition theorem for the functions of three variables. Then, we settle certain open problems

A new correction approach for information criteria to detect outliers in regression modeling Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200917
Emre DünderThe outliers cause wrong prediction and estimation results in regression models. Therefore, it is important to identify the outliers correctly in the context of regression analysis. Information criteria can be used to perform this task with corrections but these corrected versions of criteria require some subjective parameters. In this article, an objective correction approach is proposed within the

Some new resolvable group divisible designs Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200917
Shyam Saurabh; Kishore SinhaSome new resolvable group divisible designs not found in Clatworthy (1973 Clatworthy, W. H. 1973. Tables of twoassociateclass partially balanced designs, Gaithersburg, MD: Natl. Bur, Stand. (U.S.), Appl. Math. Ser: 63. [Google Scholar]), Sinha (1991 Sinha, K. 1991. A list of new Group divisible designs. Journal of Research of the National Institute of Standards and Technology 96:1–3.[Crossref], [Web

On the behavior of the high order stoploss transform for convolutions with some applications Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200916
Idir Arab; Milto Hadjikyriakou; Paulo Eduardo OliveiraHigh order stoploss transforms provide a risk measure that enables some flexibility on the weight given to high or low values of the risk. We interpret stoploss transforms as iterated distributions and prove a recursive representation for risks expressed as convolutions. We apply this to the case of gamma distributions with integer shape parameter, the Erlang distributions, proving that high order

Reweighting estimators for the transformation models with lengthbiased sampling data and missing covariates Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200916
Zhiping Qiu; Huijuan Ma; Jianhua ShiLengthbiased sampling data are commonly observed in crosssectional surveys and epidemiological cohort studies. Due to study design or accident, some components of the covariate vector are often missing. This article considers the statistical inference for the transformation models with lengthbiased sampling data and missing covariates. The reweighting estimating procedures are proposed for the unknown

A robust high dimensional estimation of a finite mixture of the generalized linear model Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200915
Azam Sabbaghi; Farzad EskandariRobust high dimensional estimation is one of the most important problems in statistics. In a high dimensional structure with a small number of nonzero observations, the dimension of the parameters is larger than the sample size. For modeling the sparsity of outlier response vector, we randomly selected a small number of observations and corrupted them arbitrarily. There are two distinct ways to overcome

Run sum control chart for monitoring the ratio of population means of a bivariate normal distribution Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200914
Sani Salihu Abubakar; Michael B. C. Khoo; Sajal Saha; Wei Lin TeohThis article proposes a twosided run sum ratio chart for monitoring the ratio of two normal variables. A Markov chain procedure is applied to evaluate the statistical performance of the chart by using both average run length (ARL) and expected average run length (EARL) criteria. A numerical comparison with the Shewhart ratio and synthetic ratio charts for the zero state analysis reveals that the run

Anisotropic functional deconvolution for the irregular design: A minimax study Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200913
Rida BenhaddouAnisotropic functional deconvolution model is investigated in the bivariate case when the design points ti , i = 1 , 2 , ⋯ , N , and xl , l = 1 , 2 , ⋯ , M , are irregular and follow known densities h 1, h 2, respectively. In particular, we focus on the case when the densities h 1 and h 2 have singularities, but 1 / h 1 and 1 / h 2 are still integrable on [0, 1]. We construct an adaptive wavelet estimator

Variable sampling interval EWMA chart for multivariate coefficient of variation Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200910
Heba N. Ayyoub; Michael B. C. Khoo; Sajal Saha; Ming Ha LeeA control chart for monitoring the multivariate coefficient of variation (MCV) is used when the focus is on monitoring the ratio of relative multivariate variability to the mean of a multivariate process. The MCV chart is useful in process monitoring when practitioners are not interested in the consistency of the mean vector or covariance matrix. This study proposes a onesided upward variable sampling

Generalized MittagLeffler Lévy process and its connections to first passage times of Lévy subordinators Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200910
Janusz GajdaIn this article, we introduce generalized MittagLeffler Lévy (GMLL) process. GMLL distribution is represented as a general Lévy subordinator delayed by a gamma process. We show various properties of this new process like it’s corresponding Lévy density function and the socalled longrange dependence property. We provide also an explicit representation for the cumulative density function (CDF) for

Developed cosine similarity measure on belief function theory: An application in medical diagnosis Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200910
Fereshteh Khalaj; Mehran KhalajIn this study, we consider a new aspect of belief function or DempsterShafer theory to define a belief set and cosine similarity measure between two belief sets under uncertainty. For this purpose, firstly, the concept of belief sets will be represented as a triple vector space that is characterized by truthbelief degree, uncertaintybelief degree; and falsitybelief degree. Then, the cosine similarity

NeymanScott process with skewnormal clusters Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200910
Nader Najar; Mohammad Q. Vahidi Asl; Abdollah JalilianIn the real world, there are point patterns where the offspring points are asymmetrically scattered around the parent points and have skewness in their locations. However, the existing distributions for the offspring locations in NeymanScott processes are usually assumed to be without any skewness in the clusters. This paper introduces a generalization of the Thomas process where the offspring points

Estimation of population variance in successive sampling in presence and absence of measurement error Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200910
Pitambar Das; Garib Nath Singh; Arnab BandyopadhyayThe present investigation deals with the estimation of population variance in successive sampling in presence and absence of measurement error. We have suggested a chain type estimator of population variance and compared its performances with natural sample variance estimator in presence and absence of measurement errors. The dominance of the proposed strategies over conventional ones has been demonstrated

Hybrid method based on neural networks and Monte Carlo simulation in view of a tradeoff between accuracy and computational time Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200910
Yacin Jerbi; Samira ChaabeneThe aim of this article is to introduce a hybrid method, based on the combination of Monte Carlo simulation and neural networks, which ensures for a general model an optimal compromise between accuracy and computing time. The major contribution of this work is that the aforesaid improvements are made whatever the hypotheses adopted to simplify the reality of the studied problem. In this article, this

Hybrid exponentially weighted moving average control chart using Bayesian approach Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200909
Surria Noor; Muhammad NoorulAmin; Muhammad Mohsin; Azaz AhmedA control chart is an important tool to monitor an industrial process and the use of prior knowledge by Bayesian theory can be helpful incontrol charting. In this paper, we have used the Bayesian approach with two different loss function (LF) symmetric and asymmetric loss function namely Linex LF and squared error LF under informative (conjugate) prior and non informative prior (uniform and Jeffery

Does how long observing correlate with upper record value? Fukushima nuclear disaster’s radiation levels are illustrated Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200908
Ramalingam ShanmugamIn this paper, an expression for computing the Pearson’s correlation coefficient between the random upper record value, X and the random number of observations, Y is obtained. Also derived are theoretical results for the joint bivariate probability function (pf) of X and Y , their marginal pf, and an alternate expression (to the correlation coefficient) measuring their dependence, where the support

A new Liutype estimator in binary logistic regression models Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200908
Esra Ertan; Kadri Ulaş AkayIn logistic regression models, the maximum likelihood method is commonly used to estimate the model parameters. However, unstable parameter estimates are obtained as a result of multicollinearity. In this article, a new biased estimator is proposed to combat multicollinearity in the binary logistic regression models. The proposed estimator is a general estimator which includes other biased estimators

Stationary queue and server content distribution of a batchsizedependent service queue with batch Markovian arrival process: BMAP / G n ( a , b ) / 1 Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200906
S. Pradhan; U. C. GuptaQueueing systems with batch Markovian arrival process (BMAP) have paramount applications in the domain of wireless communication. The BMAP has been used to model the superposition of video sources and to approximate the superposition of data, voice and video traffic. This article analyzes an infinitebuffer generally distributed batchservice queue with BMAP, general bulk service (a, b) rule and

On construction of equireplicated constant blocksum designs Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200904
Ravindra KhattreeIt is shown that in general, with arbitrary levels of quantitative treatment factor, the constant blocksum balanced incomplete block designs do not exist. I then provide, assuming it exists, a general approach to construct a constant blocksum equireplicated block design, possibly with unequally spaced treatments, from the incidence matrix of a block design with same parameters but without constant

A new method for multisample highdimensional covariance matrices test based on permutation Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200903
Wei YuFor multisample covariance testing, the classical likelihood ratio test is often efficient and powerful in lowdimensional normal cases. However, when the dimension is larger than the sample size, it fails to work in practice and theory. This paper proposes a permutation based test to handle highdimensional covariance testing problem with more than two samples. Numerical studies show that the test

The k nearest neighbors smoothing of the relativeerror regression with functional regressor Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200903
Ibrahim M. Almanjahie; Khlood A. Aissiri; Ali Laksaci; Zouaoui Chikr ElmezouarThis paper deals with the problem of the nonparametric analysis by the relativeerror regression when the explanatory of a variable is of infinite dimension. Based on kNearest Neighbors procedure (kNN), we construct an estimator and establish its asymptotic properties. Precisely, we show its Uniform consistency in Number of Neighbors (UNN) with the precision of the convergence rate. Some empirical

Twocomponent generalized bentcable models Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200903
Getachew A. DagneThis paper presents an innovative Bayesian method for assessing the status and progression of HIV infection using biomarkers such as the CD4 count and viral load variables. A distribution of viral loads in subjects starting antiretroviral treatment and followed over time may show a mixture of two subgroups: one subgroup representing “nonprogressor” subjects and another subgroup of “progressor” subjects

Improved test for the scale parameter of the powerlaw process with incomplete failure data Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200903
J. Chumnaul; M. SepehrifarThe problem of testing the scale parameter (γ) of the powerlaw process for a single system is taken into account when dealing with incomplete failure data. In this study, the modified signed loglikelihood ratio test is introduced as a method for testing parameter γ. The accuracy of the proposed method is evaluated in the literature. For incomplete failure data, the modified signed loglikelihood

The shape of partial correlation matrices Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200903
Richard Artner; Paul P. Wellingerhof; Ginette Lafit; Tim Loossens; Wolf Vanpaemel; Francis TuerlinckxThe correlational structure of a set of variables is often conveniently described by the pairwise partial correlations as they contain the same information as the Pearson correlations with the advantage of straightforward identifications of conditional linear independence. For mathematical convenience, multiple matrix representations of the pairwise partial correlations exist in the literature but

Fisher–Rao geometry and Jeffreys prior for Pareto distribution Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200902
Mingming Li; Huafei Sun; Linyu PengIn this paper, we investigate the Fisher–Rao geometry of the twoparameter family of Pareto distribution. We prove that its geometrical structure is isometric to the Poincaré upper halfplane model, and then study the corresponding geometrical features by presenting explicit expressions for connection, curvature and geodesics. It is then applied to Bayesian inference by considering the Jeffreys prior

Optimal designing of multiple deferred (dependent) state repetitive group sampling plan for variables inspection Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200902
P. Jeyadurga; S. BalamuraliIn this paper, we propose the designing methodology of multiple deferred (dependent) state repetitive group sampling plan for lot sentencing when the quality characteristic of the product follows normal distribution. This sampling plan incorporates the features of two existing sampling plans such as multiple deferred (dependent) state sampling plan and repetitive group sampling plan. Under the proposed

Generalized differencebased weighted mixed almost unbiased liu estimator in semiparametric regression models Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200902
Fikri Akdeniz; Mahdi Roozbeh; Esra Akdeniz; Naushad Mamode KhanIn classical linear regression analysis problems, the ordinary leastsquares (OLS) estimation is the popular method to obtain the regression weights, given the essential assumptions are satisfied. However, often, in reallife studies, the response data and its associated explanatory variables do not meet the required conditions, in particular under multicollinearity, and hence results can be misleading

An extension of entropy power inequality for dependent random variables Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200902
Fatemeh Asgari; Mohammad Hossein AlamatsazThe entropy power inequality (EPI) for convolution of two independent random variables was first proposed by Shannon, C. E., 1948. However, in practice, there are many situations in which the involved random variables are not independent. In this article, considering additive noise channels, it is shown that, under some conditions, EPI holds for the case when the involved random variables are dependent

A new class of marginally regular multivariate counting processes generated by the mixture of multivariate Poisson processes Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200902
Ji Hwan Cha; F. G. BadíaIn this paper, a new class of marginally regular multivariate counting processes is developed and its stochastic properties are studied. The dependence of the proposed multivariate counting process is generated from two sources: by means of mixing and by sharing a common counting process. Even under a rather complex dependence structure, the stochastic properties of the multivariate process and its

Exponential convergence rates for the kernel bivariate distribution function estimator under NSD assumption with application to hydrology data Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200901
A. Kheyri; M. Amini; H. Jabbari; A. Bozorgnia; A. VolodinIn this paper, we study the asymptotic behavior of the kernel bivariate distribution function estimator for negatively superadditive dependent. The exponential convergence rates for the kernel estimator are investigated. Under certain regularity conditions, the optimal bandwidth rate is determined with respect to mean squared error criteria. A simulation study is used to justify the behavior of the

Stage life testing with random stage changing times Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200901
Benjamin Laumen; Erhard CramerIn progressive TypeII censoring, it is often claimed that the withdrawn items are further tested under different conditions but a model incorporating this information has not been discussed so far. Introducing the model of TypeII stage life testing, we propose an approach to include information from progressively censored units subject to additional life testing by assuming a cumulative exposure

Quantum entropy in terms of local quantum Bernoulli noises and related properties Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200831
Qi Han; Zhihe Chen; Ziqiang LuLocalization of quantum Bernoulli noises (LQBNs) are the family of local annihilation and local creation operators acting on Bernoulli functionals. In this paper, we construct a density operator ρk represented by LQBNs, and define a new quantum entropy S ( ρ k ) based on LQBNs. Furthermore, we demonstrate that this quantum entropy S ( ρ k ) also has the basic properties of von Neumann entropy, such

Errors due to departure from independence in exponential series system Commun. Stat. Theory Methods (IF 0.612) Pub Date : 20200831
Asok K. Nanda; Sanjib Gayen; Shovan ChowdhuryIn reliability and life testing, when the exponentially distributed components are put in series, it is generally assumed that the lifetimes of the components are independently distributed, which leads to some errors when in fact they are not independent. In this paper, we study the relative errors incurred in different reliability measures due to such assumptions when actually they follow some bivariate