Communications in Statistics - Simulation and Computation

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ISSN / EISSN : 0361-0918 / 1532-4141
Published by: Informa UK Limited (10.1080)
Total articles ≅ 6,156
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Latest articles in this journal

Yinan Li,
Communications in Statistics - Simulation and Computation pp 1-27; https://doi.org/10.1080/03610918.2022.2033776

Abstract:
Mixtures of two-component normal distributions (MixN) have various applications in statistical inference with flexibility in density fitting. The best estimation of the five model parameters still represents a challenge. This article proposes more accurate density fittings given a random sample in both the moment-based and likelihood-based estimation frameworks. Motivated by the excellent performance of the Quasi-Monte Carlo method in quantile estimations, we propose an innovative approach to improve the accuracy of parameter estimations by reinforcing the representativeness of observed data via the distribution-free Harrell-Davis quantile estimators. The revision on the penalized maximum likelihood method is also considered due to the unpleasant properties of the original likelihood function under MixN. The bootstrap bias-corrected moment estimators are given as another revision. A sequential algorithm for optimization (SNTO) is conducted in finding numerical solutions for the two types of parameter estimation methods. SNTO is more adapted to MixN and shows strong advantages in the likelihood-based estimation compared to the famous EM algorithm. Simulation results show that our proposed approach can effectively improve estimation accuracy and increase resistance to small sample sizes and/or high percent overlaps between two mixture components. A real data example is given to illustrate the efficiency of our proposed methods.
Fateme Rezaee,
Communications in Statistics - Simulation and Computation pp 1-16; https://doi.org/10.1080/03610918.2022.2034864

Abstract:
Gaussian copula joint models for mixed correlated longitudinal continuous and count responses with random effects are presented where the count responses have zero-inflated power series distribution. To account for associations between zero-inflated count and continuous responses, we use the Gaussian copula to indirectly specify their joint distributions. A full likelihood-based approach is applied to obtain IFM method to estimate marginal parameters marginally and share parameters jointly. In this method, we used the Monte Carlo EM algorithm to obtain the parameter estimates of Gaussian copula joint models. To illustrate the utility of the models, some simulation studies are performed. Finally, the proposed models are motivated by applying a medical data set. The data set is extracted from an observational study where the correlated responses are the continuous response of body mass index and the power series response of the number of joint damages.
Sofia Sivena,
Communications in Statistics - Simulation and Computation pp 1-25; https://doi.org/10.1080/03610918.2022.2074457

Abstract:
Student evaluations on the teaching efficiency of faculty members are significant in Higher Education because they allow decisions makers to identify potential inefficient faculty members and by making appropriate decisions, to improve the quality of the teaching process of their Institution. In this paper, we revisit the methodology framework of the previous paper of Sivena and Nikolaidis in order to expand it in various ways. More specifically, we examine in detail and evaluate through simulation, several popular types of X¯ and X˜ control charts, identifying the most suitable among them, using various statistical properties of control charts as optimization criteria. Additionally, we present two more tools that will allow Higher Education Institutions if exploited in real life, to find differences in the teaching performance between evaluated faculty members, either the latter are compared in one or more pairs. All in all, we provide Higher Education decision-makers with easy-to-use and reliable tools for monitoring the teaching process of their Institutions.
Weichao Wu,
Communications in Statistics - Simulation and Computation pp 1-18; https://doi.org/10.1080/03610918.2022.2069818

Abstract:
In this paper we study point processes on the complex plane and illustrate their uses in several statistical areas, where the quantities of interest requiring estimation involve Fourier expansions. In particular, for any problem where we can describe a quantity in terms of its Fourier expansion, we propose modeling the coefficients of the expansion using a point process on the complex plane. We utilize the Poisson complex point process and model its intensity function using log-linear and mixture models. The proposed models are exemplified via applications to general density approximation, via modeling of the characteristic function, and time series analysis, via modeling of the spectral density.
Communications in Statistics - Simulation and Computation pp 1-21; https://doi.org/10.1080/03610918.2022.2075389

Abstract:
In this article, a new kernel prediction method by using ridge regression approach is suggested to combat multicollinearity and the impacts of its existence on various views of partially linear mixed measurement error model. We derive the necessary and sufficient condition for the superiority of the linear combinations of the predictors in the sense of the matrix mean square error criterion and give the selection of the ridge biasing parameter. The asymptotic normality condition is investigated and the unknown covariance matrix of measurement errors circumstance is handled. A real data analysis together with a Monte Carlo simulation study is made to assess endorsement of the kernel ridge prediction method.
, Chun-Che Wen, Rajdeep Das, Miin-Jye Wen
Communications in Statistics - Simulation and Computation pp 1-14; https://doi.org/10.1080/03610918.2022.2074456

Abstract:
The analysis of means (ANOM) is a method that can compare the mean of each treatment with the overall mean. As one-way ANOVA, the conventional ANOM is not robust under unequal variances. We applied two inference procedures, single-stage and modified single-stage sampling, to solve heteroscedastic analysis of means (HANOM) under unbalanced design. Using proposed weighted average across groups, the influence of the unknown mean and variance are both eliminated. To validate the stability of HANOM under several scenarios of unequal variances and sample sizes, simulation studies of empirical type I error rate are conducted to test the quality of procedures. A real application is provided for illustrating these two procedures clearly. In addition, we build an user-friendly interface to show the results of the HANOM by using Shiny package in R software.
Communications in Statistics - Simulation and Computation pp 1-16; https://doi.org/10.1080/03610918.2022.2071940

Abstract:
In the correlated frailty models, it is believed that all the individuals in the population will eventually experience the event of interest. This may not always be the situation in reality. There may be a certain fraction of the population which is immune to the event and hence may not experience the event under study. For such individuals, frailty may not be active i.e., zero. Hence, frailty distribution should provide a positive mass at zero. In this article, a new correlated frailty model with compound negative binomial distribution as frailty distribution, is introduced to incorporate the non-susceptibility of individuals. The inferential problem is solved in a Bayesian framework using Markov Chain Monte Carlo methods. The proposed model is then applied to a real life data set.
Lirong Cui,
Communications in Statistics - Simulation and Computation pp 1-1; https://doi.org/10.1080/03610918.2013.875438

Abstract:
The 5th Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM 2012) was held in Nanjing, China, from November 1–3, 2012. The aim of the past APARM editions was to provide a forum for scholars in the research community, mainly, from the Asia-Pacific countries, to share the latest research results on reliability, maintainability and safety. The event in the year 2012 was the first APARM, held in the mainland of China, and was hosted by School of Economics and Management, Nanjing University of Technology (NUT). Our special thanks go to not only NUT as a financial sponsor, but also the other technical supporters. We also would like to thank the organizing committee members of APARM 2012. Without their efforts, APARM 2012 could not be successful.
Communications in Statistics - Simulation and Computation pp 1-14; https://doi.org/10.1080/03610918.2022.2069261

Abstract:
In this paper, we are interested in solving backward doubly stochastic differential equations in Lp, for any p(1,2), when the coefficients are continuous with stochastic linear growth. Via approximation and comparison theorem, the existence of Lp minimal and Lp maximal solutions are obtained.
Communications in Statistics - Simulation and Computation pp 1-14; https://doi.org/10.1080/03610918.2022.2070215

Abstract:
In this study, the inspection policy for a single-unit randomly failing system with alternating operating and inactivity periods is proposed. Failures are detected instantly for the former case, whereas in the latter case, inspections are required for failure detection. This article focuses on evaluating the general expressions for limiting availability and long-run average cost of the system undergoing periodic inspections. The distinctive characteristic of the proposed model is that the inspections are not perfect. Furthermore, it is supposed that inspection and maintenance time are non-negligible, and corrective maintenance results in as good as new unit. The optimal inspection problem is developed predicated on maximizing the availability and minimizing the cost. Numerical example of electric motor corresponding to different life distributions is also presented to justify the obtained results.
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