Introduction to Maximum Likelihood

Environmental Data Analysis: An Introduction with Examples in R  eBooks & eLearning

Posted by AvaxGenius at Dec. 20, 2020
Environmental Data Analysis: An Introduction with Examples in R

Environmental Data Analysis: An Introduction with Examples in R by Carsten Dormann
English | PDF,EPUB | 2020 | 277 Pages | ISBN : 3030550192 | 38 MB

Environmental Data Analysis is an introductory statistics textbook for environmental science. It covers descriptive, inferential and predictive statistics, centred on the Generalized Linear Model. The key idea behind this book is to approach statistical analyses from the perspective of maximum likelihood, essentially treating most analyses as (multiple) regression problems.

Introduction to Inverse Problems in Imaging, 2nd Edition  eBooks & eLearning

Posted by yoyoloit at Oct. 30, 2021
Introduction to Inverse Problems in Imaging, 2nd Edition

Introduction to Inverse Problems in Imaging; Second Edition
by Mario Bertero

English | 2021 | ISBN: ‎ 0367470055 | 358 pages | True PDF | 14.84 MB
Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB (Statistics in Practice)

Maximum Likelihood Estimation and Inference: With Examples in R, SAS and ADMB (Statistics in Practice) By Russell B. Millar
2011 | 366 Pages | ISBN: 0470094826 | PDF | 4 MB

Introduction to Statistical Modelling and Inference  eBooks & eLearning

Posted by readerXXI at Dec. 3, 2022
Introduction to Statistical Modelling and Inference

Introduction to Statistical Modelling and Inference
by Murray Aitkin
English | 2023 | ISBN: 1032105712 | 374 Pages | True ePUB | 11.8 MB

Introduction to Statistical Modelling and Inference  eBooks & eLearning

Posted by yoyoloit at Sept. 1, 2022
Introduction to Statistical Modelling and Inference

Introduction to Statistical Modelling and Inference
by Murray Aitkin

English | 2022 | ISBN: ‎ 1032105712, 978-1032105710 | 391 pages | True PDF | 19.38 MB

Maximum Likelihood Estimation with Stata, Fourth Edition  eBooks & eLearning

Posted by arundhati at April 9, 2021
Maximum Likelihood Estimation with Stata, Fourth Edition

William Gould, "Maximum Likelihood Estimation with Stata, Fourth Edition"
English | ISBN: 1597180785 | 2010 | 290 pages | PDF | 2 MB

Maximum Likelihood for Social Science: Strategies for Analysis  eBooks & eLearning

Posted by interes at May 23, 2020
Maximum Likelihood for Social Science: Strategies for Analysis

Maximum Likelihood for Social Science: Strategies for Analysis (Analytical Methods for Social Research) by Michael D. Ward and John S. Ahlquist
English | Nov 22, 2018 | ISBN: 1107185823, 1316636828 | 322 pages | PDF | 3 MB
Performance Analysis of Linear Codes under Maximum-Likelihood Decoding: A Tutorial (Foundations and Trends in Communications an

Performance Analysis of Linear Codes under Maximum-Likelihood Decoding: A Tutorial (Foundations and Trends in Communications and Information Theory) By Igal Sason, Shlomo Shamai
2006 | 236 Pages | ISBN: 1933019328 | PDF | 2 MB

Coursera - Introduction to Computational Finance and Financial Econometrics  eBooks & eLearning

Posted by ParRus at June 14, 2019
Coursera - Introduction to Computational Finance and Financial Econometrics

Coursera - Introduction to Computational Finance and Financial Econometrics
WEBRip | English | MP4 + Project files | 960 x 540 | AVC ~154 kbps | 30.919 fps
AAC | 128 Kbps | 44.1 KHz | 2 channels | Subs: English (.srt) | 25:23:27 | 3.86 GB
Genre: eLearning Video / Finance, Analysis, Mathematics, Statistics

Learn mathematical, programming and statistical tools used in the real world analysis and modeling of financial data. Apply these tools to model asset returns, measure risk, and construct optimized portfolios using the open source R programming language and Microsoft Excel.

Introductory Statistical Inference with the Likelihood Function  eBooks & eLearning

Posted by AvaxGenius at Sept. 29, 2023
Introductory Statistical Inference with the Likelihood Function

Introductory Statistical Inference with the Likelihood Function by Charles A. Rohde
English | PDF (True) | 2014 | 341 Pages | ISBN : 3319104608 | 2.5 MB

This textbook covers the fundamentals of statistical inference and statistical theory including Bayesian and frequentist approaches and methodology possible without excessive emphasis on the underlying mathematics. This book is about some of the basic principles of statistics that are necessary to understand and evaluate methods for analyzing complex data sets. The likelihood function is used for pure likelihood inference throughout the book. There is also coverage of severity and finite population sampling. The material was developed from an introductory statistical theory course taught by the author at the Johns Hopkins University’s Department of Biostatistics. Students and instructors in public health programs will benefit from the likelihood modeling approach that is used throughout the text. This will also appeal to epidemiologists and psychometricians. After a brief introduction, there are chapters on estimation, hypothesis testing, and maximum likelihood modeling. The book concludes with sections on Bayesian computation and inference. An appendix contains unique coverage of the interpretation of probability, and coverage of probability and mathematical concepts.