Symmetrical and Asymmetrical Distributions in Statistics and Data Science
| Title: | Symmetrical and Asymmetrical Distributions in Statistics and Data Science |
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| Contributors: | Johannssen, Arne, Chukhrova, Nataliya, Zhu, Quanxin |
| Publisher Information: | Basel: MDPI - Multidisciplinary Digital Publishing Institute, 2024. |
| Publication Year: | 2024 |
| Subject Terms: | one-sided EWMA X charts, variable sampling interval, monte-carlo simulation, run length, zero-state, steady-state, bivariate distribution, copula, correlation, FGM copula, maximum likelihood estimator, meta-analysis, normal distribution, half-logistic class, odd Fréchet class, entropy, simulation, estimation method, SPC, RZ, EWMA chart, TEWMA chart, VSI-TEWMA chart, discretization methods, Bayesian estimation, symmetric and asymmetric loss functions, prior distribution, simulation analysis, Monte Carlo Markov chain, goodness-of-fit measures, spatial autoregressive model (SAR), weights matrix, model selection, Akaike information criterion (AIC), maximum likelihood estimation, encouraged arrival, quality control feedback, balking, maintaining, retention, alpha power inverse Weibull distribution, hybrid Type-II censoring, ball bearing, Bayes estimator, maximum product spacing, Fréchet model, symmetric Bayes inference, MCMC techniques, maximum likelihood, reliability analysis, generalized Type-II progressive hybrid censoring, average run length, control chart, multicollinearity, regression estimator, supplementary variable, cause-specific hazard, regression model, additive hazard, modified Weibull distribution, Bayes estimate, MCMC, Gumbel Type II distribution, multi-component stress-strength model, Monte Carlo simulation, Kavya Manoharan Kumaraswamy distribution, progressive hybrid generalized type-II censoring, Bayesian and classical estimators, Metropolis–Hastings algorithm, optimal plan for progressive censoring, History, Social and ethical issues |
| More Details: | Probability distributions are a fundamental topic of statistics and data science that is highly relevant in both theory and practical applications. There are numerous probability distributions that come in many shapes and with different properties. In order to identify an appropriate distribution for modeling the statistical properties of a population of interest, one should consider the shape of the distribution as the crucial factor. In particular, the symmetry or asymmetry of the distribution plays a decisive role. This reprint is a collection of articles on a wide range of topics in the field of symmetrical and asymmetrical distributions that are relevant in statistics and data science. The proposed methods and concepts are discussed in detail and illustrated with several real-life data examples. |
| Document Type: | eBook |
| File Description: | application/octet-stream |
| Language: | English |
| ISBN: | 978-3-7258-2150-1 978-3-7258-2149-5 |
| DOI: | 10.3390/books978-3-7258-2149-5 |
| Access URL: | https://directory.doabooks.org/handle/20.500.12854/152773 https://mdpi.com/books/pdfview/book/9936 |
| Rights: | Attribution 4.0 International open access URL: http://purl.org/coar/access_right/c_abf2 URL: https://creativecommons.org/licenses/by/4.0/ |
| Notes: | ONIX_20250220_9783725821501_137 |
| Accession Number: | edsdob.20.500.12854.152773 |
| Database: | Directory of Open Access Books |
| ISBN: | 9783725821501 9783725821495 |
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| DOI: | 10.3390/books978-3-7258-2149-5 |
| Language: | English |