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INAR(1) process with weighted negative binomial Lindley distributed innovations and applications to criminal and COVID-19 data Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-04-15 Zohreh Mohammadi, Hassan S. Bakouch, Predrag M. Popović
In this study, we introduce a pliant stationary first-order integer-valued autoregressive (INAR) process with weighted negative binomial Lindley innovations. The main properties of the model are de...
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A more powerful test method for analyzing unreplicated factorial two-level experiments Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-04-12 Y. Chen
Most of existing methods for analyzing unreplicated two-level factorial designs need the assumption of effect sparsity and only perform well when the effectssparsity assumption holds. The effects-s...
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Continuous-time Markov chain approximation for pricing Asian options under rough stochastic local volatility models Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-04-12 Ziqi Lei, Qing Zhou, Weilin Xiao
We propose a general framework for pricing both discretely and continuously monitored arithmetic average Asian options whose underlying asset price satisfies the rough stochastic local volatility m...
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A comparison of nonparametric methods for multivariate two-sample tests Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-04-12 Rosa Arboretti, Elena Barzizza, Riccardo Ceccato
Comparing two multivariate populations can be challenging when the distributional forms are unknown. In such a situation, parametric test procedures are not appropriate given that they require dist...
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Contrast estimation of the Vasicek integrated diffusion process for high-frequency data Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-04-09 Shanchao Yang, Zhiyong Li, Jiaying Xie, Shuyi Luo, Xin Yang
The purpose of this paper is to study the parameter estimation of the Vasicek integrated diffusion process. Based on the contrast function, the parameter contrast estimators of the Vasicek integrat...
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From bibliometrics to text mining: exploring feature selection methods in microarray research Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-31 Guilherme Alberto Sousa Ribeiro, Rommel Melgaço Barbosa, Márcio da Cunha Reis, Nattane Luiza Costa
Text mining (TM) is a technique that aims to extract knowledge from unstructured data sources by transforming them into structured data. TM algorithms can be used to detect hidden patterns in large...
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A revisit to Pearson correlation coefficient under multiplicative distortions Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-04-02 Siming Deng, Jun Zhang, Yingcong Huang, Jiongtao Zhong, Xiaozhen Yang
We consider the estimation of Pearson correlation coefficient when two continuous variables can not be directly observed but measured with multiplicative distortion measurement errors. Different fr...
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Parameter estimation for strict arcsine distribution Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-04-02 Yeh-Ching Low, Yook-Ngor Phang, Wooi-Chen Khoo, Seng-Huat Ong
The two-parameter strict arcsine distribution as a member of the natural exponential family with cubic variance function has been shown to be a viable candidate for statistical analysis of count da...
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Simultaneous variable selection and parameters estimation for longitudinal data subject to missingness and covariates measurement error Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-04-02 Heba A. Basha, Abdelnaser S. Abdrabou, Ahmed M. Gad, Wafaa I. M. Ibrahim
Longitudinal studies are indispensable to study the change over time in a response variable. The main challenge of such studies is the presence of missing values. Another challenge in these studies...
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Multiple arbitrarily inflated Poisson regression analysis Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-31 Ihab Abusaif, Burak Kayacı, Coşkun Kuş
In this paper, a new flexible count regression analysis is proposed. For this purpose, a new modification of the Poisson distribution is introduced which generalizes the Poisson, zero-inflated Pois...
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Double sparsity garrotized kernel machine in high-dimensional partially linear model Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-31 Xinyi Zhao, Yaohua Rong, Junze Lin, Maozai Tian, Jinwen Liang
Obtaining excellent prediction accuracy in the high-dimensional partially linear model is particularly important. However, it is difficult to achieve due to the complex relationship between nonpara...
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Searching the differences through the tails of distributions using an approach based on Mahalanobis distance and percentile bootstrap Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-28 A. Fırat Özdemir, Engin Yildiztepe, Tuğçe Paksoy, Gözde Navruz
One of the main objectives of applied statistics is to determine whether two independent groups differ, and if so, to understand how they do. The Student t-test is the conventional method for doing...
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Comment on ‘generating survival times with time-varying covariates using the Lambert W function’ Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-25 J. H. McVittie
Published in Communications in Statistics - Simulation and Computation (Ahead of Print, 2024)
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Bayesian inference of a queueing system with short- or long-tailed distributions based on Hamiltonian Monte Carlo Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-21 Eman Ahmed Alawamy, Liu Yuanyuan, Yiqiang Q. Zhao
In this paper, we deal with a Bayesian inference method for estimating the parameters of the queueing system with short- or long-tailed distributions based on the No-U-Turn Sampler (NUTS), a recent...
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Platinum and palladium price forecasting through neural networks Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-21 Xiaojie Xu, Yun Zhang
To many commodity market participants, forecasts of price series represent a critical task. In this work, nonlinear autoregressive neural network models’ potential is explored for forecasting daily...
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A new over-dispersed count model based on Poisson-Geometric convolution Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-21 Anupama Nandi, Subrata Chakraborty, Aniket Biswas
A new two-parameter discrete distribution, namely the PoiG distribution, is derived by the convolution of a Poisson variate and an independently distributed geometric random variable. This distribu...
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Mean and covariance estimation of functional data streams Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-21 Mingxue Quan
Mean and covariance estimation is a critical problem in functional data analysis. With the emergence of new types of functional data, there is a growing need for more sophisticated methodologies to...
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Hypothesis testing of one sample mean vector in distributed frameworks Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-21 Bin Du, Junlong Zhao, Xin Zhang
Distributed frameworks are commonly used in the setting where data are stored in k different local machines and cannot be merged due to privacy protections or the huge sample size. For a random vec...
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MoST: model specification test by variable selection stability Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-21 Xiaonan Hu
One of the major challenges in empirical studies is to construct an appropriate statistical model that accounts for the uncertainty of statistical methods and model specifications. An improperly sp...
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Inference for compound truncated Poisson log-normal model with application to maximum precipitation data Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-18 Mohammed A. Meraou, Mohammad Z. Raqab, Debasis Kundu, Fatemah A. Alqallaf
The main objective of this paper is to propose a new general family of distributions, namely compound truncated Poisson log-normal distribution of which log-normal distribution is a special case. T...
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Sure independent screening for functional regression model Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-19 Yuan Yuan, Nedret Billor
Due to rapid advancements in computer technology, high-dimensional, big, and complex data, such as functional data, where observations are considered as curves, have emerged from many applications ...
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New simple bounds for standard normal distribution function Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-15 Enas A. Ananbeh, Omar M. Eidous
This paper presents new simple lower and upper bounds for the cumulative normal distribution function, Φ(z). The accuracy and closeness of the proposed bounds to the exact Φ(z) are investigated bas...
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A robust test approach for equality of mean vectors of two independent groups under the multivariate Behrens-Fisher problem Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-14 Hasan Bulut, Gülnur Karaosman
In multivariate statistical inference, the Hotelling T2 statistic is used to test the equality of mean vectors for two independent groups. This statistic needs the multivariate normality and homoge...
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An ensemble approach to determine the number of latent dimensions and assess its reliability Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-13 Asana Neishabouri, Michel C. Desmarais
Determining the number of latent dimensions (LD) of a data set is a ubiquitous problem, for which numerous methods have been developed. We compare some of the most effective ones on synthetic data,...
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Low and high dimensional wavelet thresholds for matrix-variate normal distribution Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-11 H. Karamikabir, A. Sanati, G. G. Hamedani
The matrix-variate normal distribution is a probability distribution that is a generalization of the multivariate normal distribution to matrix-valued random variables. In this paper, we introduce ...
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Modified method of moments for generalized Laplace distributions Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-05 Adrian Fischer, Robert E. Gaunt, Andrey Sarantsev
In this note, we consider the performance of the classic method of moments for parameter estimation of symmetric variance-gamma (generalized Laplace) distributions. We do this through both theoreti...
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Modeling clustered count data using mixed effect discrete Weibull regression model with cubic splines Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-03-05 Hanna Yoo
This paper investigates the use of mixed-effect discrete Weibull (DW) regression model with cubic splines for clustered count data. DW regression model can be used for both over and under-dispersed...
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Overlap, matching, or entropy weights: what are we weighting for? Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-29 Roland A. Matsouaka, Yi Liu, Yunji Zhou
There has been a recent surge in statistical methods for handling the lack of adequate positivity when using inverse probability weights (IPW). However, these nascent developments have raised a num...
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Construction of Six Sigma-based control chart for interval-valued data Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-28 J. Ravichandran, K. Pranavi, P. Paramanathan
Construction of control charts is straightforward if the data are real-valued. However, there are situations where data are essentially interval-valued in which each observation is represented by m...
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Bayesian analysis on a natural conjugate prior for the nonhomogeneous Poisson process with a power-law intensity under time-truncated sampling Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-28 Po-Yao Huang, Yeu-Shiang Huang
The core content in this paper discusses the Bayesian approach, which essentially estimates and predicts the reliability of a repairable system during the actual testing process. As specified in pr...
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Rescaling bootstrap variance estimation technique under dual frame surveys with unknown domain sizes Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-22 Rajeev Kumar, Anil Rai, Tauqueer Ahmad, Ankur Biswas, Prachi Misra Sahoo, Pramod Kumar Moury
Dual frame (DF) surveys are a special case of multiple frame (MF) surveys considering two frames covering the entire population. Dual frame surveys are applicable in those situations, where, one fr...
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A variable clustering approach for overdispersed high-dimensional count data using a copula-based mixture model Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-20 Alberto Brini, Abu Manju, Edwin R. van den Heuvel
In this paper, we propose a latent variable model for the analysis and clustering of high-dimensional correlated and overdispersed count data. We use a set of random effects to capture within-group...
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Partially balanced nested block designs based on 2-associate-class association schemes for test-control comparisons Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-19 Vinayaka, Rajender Parsad, B. N. Mandal
In this article, nested partially balanced treatment incomplete block (NPBTIB) designs are introduced for making test treatments-control treatment comparisons. Several methods of constructing such ...
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Confidence intervals for heterogeneity in meta-analysis of the rare binary events based on empirical likelihood-type methods Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-19 Sha Li, Weizhong Tian, Xinmin Li, Wei Ning
In meta-analysis, heterogeneity between independent studies is one of the important reference indicators for comprehensive analyses. It is usually described in terms of the variance between groups ...
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Simulation of records obtained from sequences of independent and non-identically distributed variables Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-16 Alexei Stepanov
In the present paper, we provide the density-mass functions of record times and values obtained from samples of independent and non-identically distributed random variables. By making use of these ...
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Adjustment of selection bias for clinical trials: a simulation study Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-16 Yuanyuan Lu, Henian Chen, Wei Wang, Yangxin Huang, Feng Cheng, Ellen Daley
Clinical trial selection bias is a common issue, as patients are typically not selected randomly from a target population. Various statistical approaches have been proposed to adjust for this bias,...
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Locally optimal tests against periodic linear regression in short panels Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-16 Slimane Regui, Abdelhadi Akharif, Amal Mellouk
This paper aims to detect the periodic coefficients of a Linear Regression model with Panel Data. Nonparametric locally and asymptotically optimal tests are proposed for testing the null hypothesis...
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A new cure rate model with discrete and multiple exposures Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-16 Suvra Pal
Cure rate models are mostly used to study data arising from cancer clinical trials. Its use in the context of infectious diseases has not been explored well. In 2008, Tournoud and Ecochard first pr...
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Depth-based graphical tools and related tests for multivariate multi-sample problems Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-16 Somanath D. Pawar, Digambar T. Shirke
A notion of data depth is used to measure the centrality/outlyingness of a given point with respect to a given distribution or data cloud. Several depth-based graphical tools and nonparametric test...
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Truncated composite quantile regression with covariates measurement errors Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-12 Hongxia Xu, Mengting Qin, Guoliang Fan
Truncated data and measurem ent error data are often encountered in practice. In this paper, we study two classes of truncated composite quantile regression with covariates measured with errors. We...
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Robust monitoring conditional volatility change for time series based on support vector regression Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-12 Min Hyeok Yoon, Chang Kyeom Kim, Sangyeol Lee
This study considers a robust monitoring procedure aimed at detecting an anomaly of conditional volatility from sequentially observed time series following a (nonlinear) generalized autoregressive ...
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The Zero-Inflated Poisson - Probit regression model: a new model for count data Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-06 Kim-Hung Pho, Buu-Chau Truong
This paper wishes to propose a new model for count data and it is shortly called a Zero-Inflated Poisson - Probit (ZIP-P) model. The way of setting up for this new model is also based on the tradit...
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On the performance and comparison of various memory-type control charts Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-06 Vasileios Alevizakos, Kashinath Chatterjee, Christos Koukouvinos
Several versions of the exponentially weighted moving average (EWMA) control chart, such as the generally weighted moving average (GWMA), the double, triple, and quadruple EWMA (DEWMA, TEWMA, and Q...
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Gini index based goodness-of-fit test for the Lindley distribution Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-05 Hadi Alizadeh Noughabi, Mohammad Shafaei Noughabi
In survival analysis and reliability studies the Lindley distribution has been widely used. In this article, we introduce a new goodness of fit test for the Lindley distribution based on an estimat...
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Regressive class models for machine learning algorithms to predict trajectories of repeated multinomial outcomes: an application to the activity of daily living of elderly data Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-06 R. I. Chowdhury, M. T. Hasan, S. Huda, G. Sneddon
Due to the advancement of electronic data capturing, the amount of repeated categorical data being collected and stored has increased. This massive amount of data is complex and poses significant s...
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An empirical comparison between gradient boosting methods and cox’s proportional hazards model for right-censored survival data Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-02 Peizhi Li, Yingwei Peng, Jianing Zheng
Gradient boosting methods become popular in recent years to analyze right-censored survival data where Cox’s proportional hazards model is the widely used statistical model. However, there are very...
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The impact of imputation methods on the performance of Phase I Hotelling’s T2 control chart Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-02-01 Carla Wilson, Achraf Cohen
The objective of this study was to evaluate the impact of three different methods of handling missing data on the performance of Phase I Hotelling’s T2 multivariate control chart. Using a Monte Car...
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Multi-objective mathematical programming approach for multivariate compromise allocation for stratified random sampling Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-01-30 Maha I. Mahfouz, Mahmoud M. Rashwan, Zeinab A. Khadr, Mohammed A. Ramadan
The optimal allocation of stratified sample in multivariate surveys faces two main challenges. First, optimization of the conflicting objectives of the variation of the estimates and survey cost, t...
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Efficiency gains in value-at-risk and expected shortfall estimation by using copulas and full maximum likelihood Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-01-16 Brenda Castillo-Brais, Ángel León, Juan Mora
We provide Monte Carlo evidence on the efficiency gains obtained in GARCH-based estimations of value-at-risk (VaR) and expected shortfall (ES) by incorporating dependence information through copula...
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Bootstrap tests for unbiasedness of predictors Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-01-13 Janusz Wywiał, Tomasz Szkutnik
In this paper, the analysis is focused on the unbiasedness of prediction based on a linear regression model. The accuracy of the considered predictors is measured by means of a statistical test bas...
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CluBear: a subsampling package for interactive statistical analysis with massive data on a single machine Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-01-10 Ke Xu, Yingqiu Zhu, Yijing Liu, Hansheng Wang
This article introduces CluBear, a Python-based open-source package for interactive massive data analysis. The key feature of CluBear is that it enables users to conduct convenient and interactive ...
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Regularized least weighted squares estimator in linear regression Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-01-08 Jan Kalina
This article is interested in estimating parameters of the linear regression model in a high-dimensional setting, i.e. with a large number of regressors. The lasso estimator does not possess high r...
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Convergence properties for randomly weighted sums of ρ-mixing sequences with related statistical applications Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-01-05 Shunping Zheng, Fei Zhang, Yan Shen, Xuejun Wang, Jinxiang Ou
In this paper, we investigate some convergence properties, such as complete convergence, complete moment convergence, complete f-moment convergence and strong law of large numbers, for partial sums...
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t distribution-based robust semiparametric mixture regression model Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-01-04 Yan Ge, Sijia Xiang, Weixin Yao
Semiparametric mixture of regression (SMR) models provide a popular and flexible framework for modeling heterogeneous data that violates some of the parametric assumptions assumed in traditional fi...
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Generalized asymmetric mixture normal distribution: properties and applications Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-01-03 C. Satheesh Kumar, G. V. Anila
A new class of skew generalized normal distribution as a generalization of the skew-normal distribution of Arellano-Valle (Commun. Statist. Theor. Meth., 2004) and Kumar and Anusree (Commun. Statis...
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Model detection for grey forecasting model with polynomial term Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-01-03 Zhi-yuan Ouyang, Meng Wang, Tao Zhang
A grey forecasting model with polynomial term which includes the traditional grey model (GM (1)), the nonhomogeneous grey model (NGM(1,1,k)) and the integer order grey model with a time power term ...
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Classification with Bernstein copula as discrimination function Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-01-02 Tolga Yamut, Burcu Hudaverdi
Bernstein copula models are handy tools for constructing higher-dimensional distribution structures. This study proposes a Bernstein copula model as a discrimination function to classify the given ...
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Uncertain quantile autoregressive model Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2024-01-02 Yuxin Shi, Yuhong Sheng
The propose of uncertain time series is to explore the relationship between response variables and explanatory variables over time based on the imprecise observations. In order to more comprehensiv...
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Efficient estimation for nonparametric spatio-temporal models with nonparametric autocorrelated errors⋆ Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2023-12-28 Xuehong Luo, Zihan Zhao, Hongxia Wang, Chenhua Li
Spatio-temporally correlated data appear in many environmental studies, and consequently, there is an increasing demand for estimation methods that take account of spatio-temporal (ST) correlation ...
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A new extended normal quantile regression model: properties and applications Commun. Stat. Simul. Comput. (IF 0.9) Pub Date : 2023-12-27 Gabriela M. Rodrigues, Edwin M. M. Ortega, Roberto Vila, Gauss M. Cordeiro
We propose the exponentiated odd log-logistic normal quantile regression model relating the covariates to the parameters through two systematic components, and adopt the maximum likelihood method t...