Model Selection and Multimodel Inference PDF Download
Are you looking for read ebook online? Search for your book and save it on your Kindle device, PC, phones or tablets. Download Model Selection and Multimodel Inference PDF full book. Access full book title Model Selection and Multimodel Inference by Kenneth P. Burnham. Download full books in PDF and EPUB format.
Author: Kenneth P. Burnham Publisher: Springer Science & Business Media ISBN: 0387224564 Category : Mathematics Languages : en Pages : 488
Book Description
A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.
Author: Kenneth P. Burnham Publisher: Springer Science & Business Media ISBN: 0387224564 Category : Mathematics Languages : en Pages : 488
Book Description
A unique and comprehensive text on the philosophy of model-based data analysis and strategy for the analysis of empirical data. The book introduces information theoretic approaches and focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. It contains several new approaches to estimating model selection uncertainty and incorporating selection uncertainty into estimates of precision. An array of examples is given to illustrate various technical issues. The text has been written for biologists and statisticians using models for making inferences from empirical data.
Author: Kenneth P. Burnham Publisher: Springer Science & Business Media ISBN: 1475729170 Category : Mathematics Languages : en Pages : 373
Book Description
Statisticians and applied scientists must often select a model to fit empirical data. This book discusses the philosophy and strategy of selecting such a model using the information theory approach pioneered by Hirotugu Akaike. This approach focuses critical attention on a priori modeling and the selection of a good approximating model that best represents the inference supported by the data. The book includes practical applications in biology and environmental science.
Author: Ethel Spencer Publisher: University of Pittsburgh Press ISBN: 9780822971344 Category : Biography & Autobiography Languages : en Pages : 208
Book Description
This appealing memoir introduces the family of Charles Hart Spencer and his wife Mary Acheson: seven children born between 1884 and 1895. It also introduces a large Victorian house in Shadyside (a Pittsburgh neighborhood) and a middle-class way of life at the turn of the century. Mr. Spencer, who worked--not very happily--for Henry Clay Frick, was one of the growing number of middle-management employees in American industrial cities in the 1880s and 1890s. His income, which supported his family of nine, a cook, two regular nurses, and at times a wet nurse and her baby, guaranteed a comfortable life but not a luxurious one. In the words of the editors, the Spencers represent a class that "too often stands silent or stereotyped as we rush forward toward the greater glamour of the robber barons or their immigrant workers." Through the eyes of Ethel Spencer, the third daughter, we are led with warmth and humor through the routine of everyday life in this household: school, play, church on Sundays, illness, family celebrations, and vacations. Ethel was an observant child, with little sentimentality, and she wrote her memoir in later life as a professor of English with a gift for clear prose and the instincts of an anthropologist. As the editors observe, her memoir is "a fascinating insight into one kind of urban life of three generations ago."
Author: C.S. Wallace Publisher: Springer Science & Business Media ISBN: 9780387237954 Category : Computers Languages : en Pages : 456
Book Description
The Minimum Message Length (MML) Principle is an information-theoretic approach to induction, hypothesis testing, model selection, and statistical inference. MML, which provides a formal specification for the implementation of Occam's Razor, asserts that the ‘best’ explanation of observed data is the shortest. Further, an explanation is acceptable (i.e. the induction is justified) only if the explanation is shorter than the original data. This book gives a sound introduction to the Minimum Message Length Principle and its applications, provides the theoretical arguments for the adoption of the principle, and shows the development of certain approximations that assist its practical application. MML appears also to provide both a normative and a descriptive basis for inductive reasoning generally, and scientific induction in particular. The book describes this basis and aims to show its relevance to the Philosophy of Science. Statistical and Inductive Inference by Minimum Message Length will be of special interest to graduate students and researchers in Machine Learning and Data Mining, scientists and analysts in various disciplines wishing to make use of computer techniques for hypothesis discovery, statisticians and econometricians interested in the underlying theory of their discipline, and persons interested in the Philosophy of Science. The book could also be used in a graduate-level course in Machine Learning and Estimation and Model-selection, Econometrics and Data Mining. C.S. Wallace was appointed Foundation Chair of Computer Science at Monash University in 1968, at the age of 35, where he worked until his death in 2004. He received an ACM Fellowship in 1995, and was appointed Professor Emeritus in 1996. Professor Wallace made numerous significant contributions to diverse areas of Computer Science, such as Computer Architecture, Simulation and Machine Learning. His final research focused primarily on the Minimum Message Length Principle.
Author: Deborah G. Mayo Publisher: Cambridge University Press ISBN: 1108563309 Category : Mathematics Languages : en Pages : 503
Book Description
Mounting failures of replication in social and biological sciences give a new urgency to critically appraising proposed reforms. This book pulls back the cover on disagreements between experts charged with restoring integrity to science. It denies two pervasive views of the role of probability in inference: to assign degrees of belief, and to control error rates in a long run. If statistical consumers are unaware of assumptions behind rival evidence reforms, they can't scrutinize the consequences that affect them (in personalized medicine, psychology, etc.). The book sets sail with a simple tool: if little has been done to rule out flaws in inferring a claim, then it has not passed a severe test. Many methods advocated by data experts do not stand up to severe scrutiny and are in tension with successful strategies for blocking or accounting for cherry picking and selective reporting. Through a series of excursions and exhibits, the philosophy and history of inductive inference come alive. Philosophical tools are put to work to solve problems about science and pseudoscience, induction and falsification.
Author: David R. Anderson Publisher: Springer Science & Business Media ISBN: 0387740759 Category : Science Languages : en Pages : 184
Book Description
This textbook introduces a science philosophy called "information theoretic" based on Kullback-Leibler information theory. It focuses on a science philosophy based on "multiple working hypotheses" and statistical models to represent them. The text is written for people new to the information-theoretic approaches to statistical inference, whether graduate students, post-docs, or professionals. Readers are however expected to have a background in general statistical principles, regression analysis, and some exposure to likelihood methods. This is not an elementary text as it assumes reasonable competence in modeling and parameter estimation.
Author: Chester Ismay Publisher: CRC Press ISBN: 1000763463 Category : Mathematics Languages : en Pages : 461
Book Description
Statistical Inference via Data Science: A ModernDive into R and the Tidyverse provides a pathway for learning about statistical inference using data science tools widely used in industry, academia, and government. It introduces the tidyverse suite of R packages, including the ggplot2 package for data visualization, and the dplyr package for data wrangling. After equipping readers with just enough of these data science tools to perform effective exploratory data analyses, the book covers traditional introductory statistics topics like confidence intervals, hypothesis testing, and multiple regression modeling, while focusing on visualization throughout. Features: ● Assumes minimal prerequisites, notably, no prior calculus nor coding experience ● Motivates theory using real-world data, including all domestic flights leaving New York City in 2013, the Gapminder project, and the data journalism website, FiveThirtyEight.com ● Centers on simulation-based approaches to statistical inference rather than mathematical formulas ● Uses the infer package for "tidy" and transparent statistical inference to construct confidence intervals and conduct hypothesis tests via the bootstrap and permutation methods ● Provides all code and output embedded directly in the text; also available in the online version at moderndive.com This book is intended for individuals who would like to simultaneously start developing their data science toolbox and start learning about the inferential and modeling tools used in much of modern-day research. The book can be used in methods and data science courses and first courses in statistics, at both the undergraduate and graduate levels.
Author: Kenneth P. Burnham
Author: Kenneth P. Burnham
Author: Kenneth P. Burnham
Author: Kenneth P. Burnham
Author: Ethel Spencer
Author: Kenneth P. Burnham
Author: Gerda Claeskens
Author: C.S. Wallace
Author: Deborah G. Mayo
Author: David R. Anderson
Author: Chester Ismay