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Mathematics
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Statistics 2020
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Statistics 2020

A special issue of Mathematics (ISSN 2227-7390). This special issue belongs to the section "Probability and Statistics".

Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 24963

Special Issue Editor

Dr. Christophe Chesneau

E-Mail Website
Guest Editor
Department of Mathematics, Université de Caen, LMNO, Campus II, Science 3, 14032 Caen, France
Interests: mathematical statistics; applied statistics; data analysis; probability; applied probability; analytic inequalities
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The aim of this Special Issue is to publish original research articles that cover recent advances in all the facets of statistics. Primary emphasis is placed on strongly motivated, well written, complete, and original papers.

The scope includes, but is not limited to, the following topics:

Biostatistics;

Data analysis;

Dimension reduction and variable selection;

Financial statistics and econometrics;

Inference with high-dimensional data;

Inference of stochastic processes;

Machine learning;

Nonparametric function estimation;

Nonparametric modeling;

Nonparametric Bayes methods;

Sample surveys;

Semiparametric models and procedures;

Statistical algorithms;

Statistical distributions;

Statistical methods for imaging and tomography;

Time series analysis

Dr. Christophe Chesneau
Guest Editor

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Published Papers (8 papers)

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Research

15 pages, 879 KiB  
Article
The Inverse-Power Logistic-Exponential Distribution: Properties, Estimation Methods, and Application to Insurance Data
by Mashail M. AL Sobhi
Mathematics 2020, 8(11), 2060; https://doi.org/10.3390/math8112060 - 18 Nov 2020
Cited by 7 | Viewed by 2501
Abstract
The present paper proposes a new distribution called the inverse power logistic exponential distribution that extends the inverse Weibull, inverse logistic exponential, inverse Rayleigh, and inverse exponential distributions. The proposed model accommodates symmetrical, right-skewed, left-skewed, reversed-J-shaped, and J-shaped densities and increasing, unimodal, decreasing, [...] Read more.
The present paper proposes a new distribution called the inverse power logistic exponential distribution that extends the inverse Weibull, inverse logistic exponential, inverse Rayleigh, and inverse exponential distributions. The proposed model accommodates symmetrical, right-skewed, left-skewed, reversed-J-shaped, and J-shaped densities and increasing, unimodal, decreasing, reversed-J-shaped, and J-shaped hazard rates. We derive some mathematical properties of the proposed model. The model parameters were estimated using five estimation methods including the maximum likelihood, Anderson–Darling, least-squares, Cramér–von Mises, and weighted least-squares estimation methods. The performance of these estimation methods was assessed by a detailed simulation study. Furthermore, the flexibility of the introduced model was studied using an insurance real dataset, showing that the proposed model can be used to fit the insurance data as compared with twelve competing models. Full article
(This article belongs to the Special Issue Statistics 2020)
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28 pages, 1105 KiB  
Article
A New Kumaraswamy Generalized Family of Distributions with Properties, Applications, and Bivariate Extension
by Muhammad H. Tahir, Muhammad Adnan Hussain, Gauss M. Cordeiro, M. El-Morshedy and M. S. Eliwa
Mathematics 2020, 8(11), 1989; https://doi.org/10.3390/math8111989 - 7 Nov 2020
Cited by 34 | Viewed by 4263
Abstract
For bounded unit interval, we propose a new Kumaraswamy generalized (G) family of distributions through a new generator which could be an alternate to the Kumaraswamy-G family proposed earlier by Cordeiro and de Castro in 2011. This new generator can also be used [...] Read more.
For bounded unit interval, we propose a new Kumaraswamy generalized (G) family of distributions through a new generator which could be an alternate to the Kumaraswamy-G family proposed earlier by Cordeiro and de Castro in 2011. This new generator can also be used to develop alternate G-classes such as beta-G, McDonald-G, Topp-Leone-G, Marshall-Olkin-G, and Transmuted-G for bounded unit interval. Some mathematical properties of this new family are obtained and maximum likelihood method is used for the estimation of G-family parameters. We investigate the properties of one special model called the new Kumaraswamy-Weibull (NKwW) distribution. Parameters of NKwW model are estimated by using maximum likelihood method, and the performance of these estimators are assessed through simulation study. Two real life data sets are analyzed to illustrate the importance and flexibility of the proposed model. In fact, this model outperforms some generalized Weibull models such as the Kumaraswamy-Weibull, McDonald-Weibull, beta-Weibull, exponentiated-generalized Weibull, gamma-Weibull, odd log-logistic-Weibull, Marshall-Olkin-Weibull, transmuted-Weibull and exponentiated-Weibull distributions when applied to these data sets. The bivariate extension of the family is also proposed, and the estimation of parameters is dealt. The usefulness of the bivariate NKwW model is illustrated empirically by means of a real-life data set. Full article
(This article belongs to the Special Issue Statistics 2020)
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26 pages, 3733 KiB  
Article
The Odd Exponentiated Half-Logistic Exponential Distribution: Estimation Methods and Application to Engineering Data
by Maha A. D. Aldahlan and Ahmed Z. Afify
Mathematics 2020, 8(10), 1684; https://doi.org/10.3390/math8101684 - 1 Oct 2020
Cited by 16 | Viewed by 1878
Abstract
In this paper, we studied the problem of estimating the odd exponentiated half-logistic exponential (OEHLE) parameters using several frequentist estimation methods. Parameter estimation provides a guideline for choosing the best method of estimation for the model parameters, which would be very important for [...] Read more.
In this paper, we studied the problem of estimating the odd exponentiated half-logistic exponential (OEHLE) parameters using several frequentist estimation methods. Parameter estimation provides a guideline for choosing the best method of estimation for the model parameters, which would be very important for reliability engineers and applied statisticians. We considered eight estimation methods, called maximum likelihood, maximum product of spacing, least squares, Cramér–von Mises, weighted least squares, percentiles, Anderson–Darling, and right-tail Anderson–Darling for estimating its parameters. The finite sample properties of the parameter estimates are discussed using Monte Carlo simulations. In order to obtain the ordering performance of these estimators, we considered the partial and overall ranks of different estimation methods for all parameter combinations. The results illustrate that all classical estimators perform very well and their performance ordering, based on overall ranks, from best to worst, is the maximum product of spacing, maximum likelihood, Anderson–Darling, percentiles, weighted least squares, least squares, right-tail Anderson–Darling, and Cramér–von-Mises estimators for all the studied cases. Finally, the practical importance of the OEHLE model was illustrated by analysing a real data set, proving that the OEHLE distribution can perform better than some well known existing extensions of the exponential distribution. Full article
(This article belongs to the Special Issue Statistics 2020)
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19 pages, 308 KiB  
Article
Inference from Non-Probability Surveys with Statistical Matching and Propensity Score Adjustment Using Modern Prediction Techniques
by Luis Castro-Martín, Maria del Mar Rueda and Ramón Ferri-García
Mathematics 2020, 8(6), 879; https://doi.org/10.3390/math8060879 - 1 Jun 2020
Cited by 10 | Viewed by 3598
Abstract
Online surveys are increasingly common in social and health studies, as they provide fast and inexpensive results in comparison to traditional ones. However, these surveys often work with biased samples, as the data collection is often non-probabilistic because of the lack of internet [...] Read more.
Online surveys are increasingly common in social and health studies, as they provide fast and inexpensive results in comparison to traditional ones. However, these surveys often work with biased samples, as the data collection is often non-probabilistic because of the lack of internet coverage in certain population groups and the self-selection procedure that many online surveys rely on. Some procedures have been proposed to mitigate the bias, such as propensity score adjustment (PSA) and statistical matching. In PSA, propensity to participate in a nonprobability survey is estimated using a probability reference survey, and then used to obtain weighted estimates. In statistical matching, the nonprobability sample is used to train models to predict the values of the target variable, and the predictions of the models for the probability sample can be used to estimate population values. In this study, both methods are compared using three datasets to simulate pseudopopulations from which nonprobability and probability samples are drawn and used to estimate population parameters. In addition, the study compares the use of linear models and Machine Learning prediction algorithms in propensity estimation in PSA and predictive modeling in Statistical Matching. The results show that statistical matching outperforms PSA in terms of bias reduction and Root Mean Square Error (RMSE), and that simpler prediction models, such as linear and k-Nearest Neighbors, provide better outcomes than bagging algorithms. Full article
(This article belongs to the Special Issue Statistics 2020)
10 pages, 1092 KiB  
Article
Determination of the Factors Affecting King Abdul Aziz University Published Articles in ISI by Multilayer Perceptron Artificial Neural Network
by Rashad A. R. Bantan, Ramadan A. Zeineldin, Farrukh Jamal and Christophe Chesneau
Mathematics 2020, 8(5), 766; https://doi.org/10.3390/math8050766 - 11 May 2020
Cited by 1 | Viewed by 2114
Abstract
Deanship of scientific research established by the King Abdulaziz University provides some research programs for its staff and researchers and encourages them to submit proposals in this regard. Distinct research study (DRS) is one of these programs. It is available all the year [...] Read more.
Deanship of scientific research established by the King Abdulaziz University provides some research programs for its staff and researchers and encourages them to submit proposals in this regard. Distinct research study (DRS) is one of these programs. It is available all the year and the King Abdulaziz University (KAU) staff can submit more than one proposal at the same time up to three proposals. The rules of the DSR program are simple and easy so it contributes in increasing the international rank of KAU. The authors are offered financial and moral reward after publishing articles from these proposals in Thomson-ISI journals. In this paper, multiplayer perceptron (MLP) artificial neural network (ANN) is employed to determine the factors that have more effect on the number of ISI published articles. The proposed study used real data of the finished projects from 2011 to April 2019. Full article
(This article belongs to the Special Issue Statistics 2020)
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12 pages, 850 KiB  
Article
A Hidden Markov Model to Address Measurement Errors in Ordinal Response Scale and Non-Decreasing Process
by Lizbeth Naranjo, Luz Judith R. Esparza and Carlos J. Pérez
Mathematics 2020, 8(4), 622; https://doi.org/10.3390/math8040622 - 17 Apr 2020
Cited by 5 | Viewed by 2973
Abstract
A Bayesian approach was developed, tested, and applied to model ordinal response data in monotone non-decreasing processes with measurement errors. An inhomogeneous hidden Markov model with continuous state-space was considered to incorporate measurement errors in the categorical response at the same time that [...] Read more.
A Bayesian approach was developed, tested, and applied to model ordinal response data in monotone non-decreasing processes with measurement errors. An inhomogeneous hidden Markov model with continuous state-space was considered to incorporate measurement errors in the categorical response at the same time that the non-decreasing patterns were kept. The computational difficulties were avoided by including latent variables that allowed implementing an efficient Markov chain Monte Carlo method. A simulation-based analysis was carried out to validate the approach, whereas the proposed approach was applied to analyze aortic aneurysm progression data. Full article
(This article belongs to the Special Issue Statistics 2020)
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20 pages, 6632 KiB  
Article
Application of Mixed Sampling to Real Life Data: A Case Study on Socio-Economic Determinants by Using SEM and CFA Techniques
by Muhammad Akbar Ali Shah, Wali Khan Mashwani, Wiyada Kumam, Poom Kumam, Christophe Chesneau, Farrukh Jamal, Gamze Ozel, Hafiza Shumaila Sleem and Hidayat Ullah Khan
Mathematics 2020, 8(3), 337; https://doi.org/10.3390/math8030337 - 3 Mar 2020
Cited by 2 | Viewed by 3358
Abstract
The objective of this study is to highlight the stress factors influencing primary school female teachers in southern Punjab, Pakistan. A causation model is developed to determine the effect of the three main domains of stress. Data were collected through a questionnaire using [...] Read more.
The objective of this study is to highlight the stress factors influencing primary school female teachers in southern Punjab, Pakistan. A causation model is developed to determine the effect of the three main domains of stress. Data were collected through a questionnaire using a convenient sampling technique. Cronbach’s alpha is computed to determine the internal consistency of the items of the questionnaire. The factors involved in the causation model are confirmed through confirmatory factor analysis. The perceived stress scale is used to check the stress level in primary school female teachers. A structural pathway of social, health and environmental factors is designed to determine the influence of different variables on stress. The examined problems included the four following major areas: social factors, economic factors, health factors and environment factors. Among our results, it is shown that the marital status has an effect on the stress level of both public and private female school teachers. Full article
(This article belongs to the Special Issue Statistics 2020)
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23 pages, 1661 KiB  
Article
A Simultaneous Stochastic Frontier Model with Dependent Error Components and Dependent Composite Errors: An Application to Chinese Banking Industry
by Jianxu Liu, Mengjiao Wang, Ji Ma, Sanzidur Rahman and Songsak Sriboonchitta
Mathematics 2020, 8(2), 238; https://doi.org/10.3390/math8020238 - 13 Feb 2020
Cited by 5 | Viewed by 2979
Abstract
The paper develops a simultaneous equations stochastic frontier model (SFM) with dependent random noise and inefficiency components of individual equations as well as allowing dependence across all equations of the model using copula functions. First, feasibility of our developed model was verified via [...] Read more.
The paper develops a simultaneous equations stochastic frontier model (SFM) with dependent random noise and inefficiency components of individual equations as well as allowing dependence across all equations of the model using copula functions. First, feasibility of our developed model was verified via two simulation studies. Then the model was applied to assess cost efficiency and market power of the banking industry of China using a panel data of 37 banks covering the period 2013–2018. Results confirmed that our simultaneous SFM with dependent random noise and inefficiency components outperformed its predecessor, which is a simultaneous SFM with dependent composite errors but with independent random noise and inefficiency components of individual SFMs as well as the conventional single-equation SFM. Apart from the statistical and computational superiority of our developed model, we also see that Chinese banks in general have a high level of cost efficiency and that competition in the banking industry of China mainly exists in state-owned banks and joint stock banks. Presence of economies of scales as well as diseconomies of scales were found in different banks. Also, the state-owned banks embraced most sophisticated technologies thereby allowing them to operate with the highest level of cost efficiency. Full article
(This article belongs to the Special Issue Statistics 2020)
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