Distribution For Modelling Location Scale And Shape

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Distributions For Modeling Location Scale And Shape

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Author : Robert A. Rigby
language : en
Publisher: CRC Press
Release Date : 2019-10-08

Distributions For Modeling Location Scale And Shape written by Robert A. Rigby and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-08 with Mathematics categories.

This is a book about statistical distributions, their properties, and their application to modelling the dependence of the location, scale, and shape of the distribution of a response variable on explanatory variables. It will be especially useful to applied statisticians and data scientists in a wide range of application areas, and also to those interested in the theoretical properties of distributions. This book follows the earlier book ‘Flexible Regression and Smoothing: Using GAMLSS in R’, [Stasinopoulos et al., 2017], which focused on the GAMLSS model and software. GAMLSS (the Generalized Additive Model for Location, Scale, and Shape, [Rigby and Stasinopoulos, 2005]), is a regression framework in which the response variable can have any parametric distribution and all the distribution parameters can be modelled as linear or smooth functions of explanatory variables. The current book focuses on distributions and their application. Key features: Describes over 100 distributions, (implemented in the GAMLSS packages in R), including continuous, discrete and mixed distributions. Comprehensive summary tables of the properties of the distributions. Discusses properties of distributions, including skewness, kurtosis, robustness and an important classification of tail heaviness. Includes mixed distributions which are continuous distributions with additional specific values with point probabilities. Includes many real data examples, with R code integrated in the text for ease of understanding and replication. Supplemented by the gamlss website. This book will be useful for applied statisticians and data scientists in selecting a distribution for a univariate response variable and modelling its dependence on explanatory variables, and to those interested in the properties of distributions.

Distribution For Modelling Location Scale And Shape

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Author : Robert A. Rigby
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2019-09-20

Distribution For Modelling Location Scale And Shape written by Robert A. Rigby and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-09-20 with Big data categories.

"This is the second volume in a series of books about using the GAMLSS R package developed by the authors. This volume presents a broad overview of statistical distributions and how they can be used in practical applications. It describes over 100 distributions - all available in the supporting R package - including their properties, limitations, and applications. Given the increasing size and complexity of available datasets, it is important to choose the underlying statistical distribution for your model very carefully, and this book gives both users and non-users of GAMLSS the tools to do that effectively"--

Generalized Additive Models For Location Scale And Shape

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Author : Mikis D. Stasinopoulos
language : en
Publisher: Cambridge University Press
Release Date : 2024-02-29

Generalized Additive Models For Location Scale And Shape written by Mikis D. Stasinopoulos and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-29 with Mathematics categories.

An emerging field in statistics, distributional regression facilitates the modelling of the complete conditional distribution, rather than just the mean. This book introduces generalized additive models for location, scale and shape (GAMLSS) – one of the most important classes of distributional regression. Taking a broad perspective, the authors consider penalized likelihood inference, Bayesian inference, and boosting as potential ways of estimating models and illustrate their usage in complex applications. Written by the international team who developed GAMLSS, the text's focus on practical questions and problems sets it apart. Case studies demonstrate how researchers in statistics and other data-rich disciplines can use the model in their work, exploring examples ranging from fetal ultrasounds to social media performance metrics. The R code and data sets for the case studies are available on the book's companion website, allowing for replication and further study.

Statistical Distributions

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Author : Nick T. Thomopoulos
language : en
Publisher: Springer
Release Date : 2017-10-10

Statistical Distributions written by Nick T. Thomopoulos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-10 with Mathematics categories.

This book gives a description of the group of statistical distributions that have ample application to studies in statistics and probability. Understanding statistical distributions is fundamental for researchers in almost all disciplines. The informed researcher will select the statistical distribution that best fits the data in the study at hand. Some of the distributions are well known to the general researcher and are in use in a wide variety of ways. Other useful distributions are less understood and are not in common use. The book describes when and how to apply each of the distributions in research studies, with a goal to identify the distribution that best applies to the study. The distributions are for continuous, discrete, and bivariate random variables. In most studies, the parameter values are not known a priori, and sample data is needed to estimate parameter values. In other scenarios, no sample data is available, and the researcher seeks some insight that allows the estimate of the parameter values to be gained. This handbook of statistical distributions provides a working knowledge of applying common and uncommon statistical distributions in research studies. These nineteen distributions are: continuous uniform, exponential, Erlang, gamma, beta, Weibull, normal, lognormal, left-truncated normal, right-truncated normal, triangular, discrete uniform, binomial, geometric, Pascal, Poisson, hyper-geometric, bivariate normal, and bivariate lognormal. Some are from continuous data and others are from discrete and bivariate data. This group of statistical distributions has ample application to studies in statistics and probability and practical use in real situations. Additionally, this book explains computing the cumulative probability of each distribution and estimating the parameter values either with sample data or without sample data. Examples are provided throughout to guide the reader. Accuracy in choosing and applying statistical distributions is particularly imperative for anyone who does statistical and probability analysis, including management scientists, market researchers, engineers, mathematicians, physicists, chemists, economists, social science researchers, and students in many disciplines.

Generalized Linear Models For Insurance Data

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Author : Piet de Jong
language : en
Publisher: Cambridge University Press
Release Date : 2008-04-02

Generalized Linear Models For Insurance Data written by Piet de Jong and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-04-02 with Business & Economics categories.

All techniques illustrated on data sets relevant to insurance; SAS code and output, data sets, exercise solutions on website

Statistics And Data Analysis For Financial Engineering

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Author : David Ruppert
language : en
Publisher: Springer
Release Date : 2015-04-21

Statistics And Data Analysis For Financial Engineering written by David Ruppert and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-21 with Business & Economics categories.

The new edition of this influential textbook, geared towards graduate or advanced undergraduate students, teaches the statistics necessary for financial engineering. In doing so, it illustrates concepts using financial markets and economic data, R Labs with real-data exercises, and graphical and analytic methods for modeling and diagnosing modeling errors. These methods are critical because financial engineers now have access to enormous quantities of data. To make use of this data, the powerful methods in this book for working with quantitative information, particularly about volatility and risks, are essential. Strengths of this fully-revised edition include major additions to the R code and the advanced topics covered. Individual chapters cover, among other topics, multivariate distributions, copulas, Bayesian computations, risk management, and cointegration. Suggested prerequisites are basic knowledge of statistics and probability, matrices and linear algebra, and calculus. There is an appendix on probability, statistics and linear algebra. Practicing financial engineers will also find this book of interest.

Financial Statistics

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Author : Mr. Rohit Manglik
language : en
Publisher: EduGorilla Publication
Release Date : 2024-07-17

Financial Statistics written by Mr. Rohit Manglik and has been published by EduGorilla Publication this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-17 with Business & Economics categories.

EduGorilla Publication is a trusted name in the education sector, committed to empowering learners with high-quality study materials and resources. Specializing in competitive exams and academic support, EduGorilla provides comprehensive and well-structured content tailored to meet the needs of students across various streams and levels.

Navigating The Technological Tide The Evolution And Challenges Of Business Model Innovation

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Author : Bahaaeddin Alareeni
language : en
Publisher: Springer Nature
Release Date : 2024-07-31

Navigating The Technological Tide The Evolution And Challenges Of Business Model Innovation written by Bahaaeddin Alareeni and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-31 with Technology & Engineering categories.

In an era defined by technological breakthroughs such as AI, blockchain, and IoT, this book offers a fresh and practical approach to Business Model Innovation (BMI). It delves into how technological advancements drive new business models and enhance operational efficiency, providing actionable insights and real-world examples for business leaders, strategists, operations managers, entrepreneurs, and students in business and technology disciplines. Encouraging diverse research methods, including theoretical, empirical, and multimethod studies, it welcomes manuscripts with clear managerial or policy implications. Aimed at students, scholars, researchers, professionals, executives, government agencies, and policymakers, this book equips readers with tools to succeed in today's dynamic business environment and supports multidisciplinary research to advance innovation management practices.

Computational Methods For Optimizing Manufacturing Technology Models And Techniques

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Author : Davim, J. Paulo
language : en
Publisher: IGI Global
Release Date : 2012-02-29

Computational Methods For Optimizing Manufacturing Technology Models And Techniques written by Davim, J. Paulo and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-29 with Technology & Engineering categories.

"This book contains the latest research developments in manufacturing technology and its optimization, and demonstrates the fundamentals of new computational approaches and the range of their potential application"--Provided by publisher.

Data Science For Wind Energy

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Author : Yu Ding
language : en
Publisher: CRC Press
Release Date : 2019-06-04

Data Science For Wind Energy written by Yu Ding and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-04 with Business & Economics categories.

Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Please also visit the author’s book site at https://aml.engr.tamu.edu/book-dswe. Features Provides an integral treatment of data science methods and wind energy applications Includes specific demonstration of particular data science methods and their use in the context of addressing wind energy needs Presents real data, case studies and computer codes from wind energy research and industrial practice Covers material based on the author's ten plus years of academic research and insights