A Practical Introduction to Regression Discontinuity Designs: Extensions
English | 2024 | ISBN: 1009462326 | 122 Pages | PDF (True) | 4 MB
English | 2024 | ISBN: 1009462326 | 122 Pages | PDF (True) | 4 MB
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Demystifying Causal Inference: Public Policy Applications with R
Date: 1 Oct 2023 12:39:54
Demystifying Causal Inference: Public Policy Applications with R by Vikram Dayal , Anand Murugesan
English | PDF EPUB (True) | 2023 | 304 Pages | ISBN : 9819939046 | 55.5 MB
This book provides an accessible introduction to causal inference and data analysis with R, specifically for a public policy audience. It aims to demystify these topics by presenting them through practical policy examples from a range of disciplines. It provides a hands-on approach to working with data in R using the popular tidyverse package. High quality R packages for specific causal inference techniques like ggdag, Matching, rdrobust, dosearch etc. are used in the book.
Generalized Linear Mixed Models with Applications in Agriculture and Biology
Date: 17 Aug 2023 06:24:16
Generalized Linear Mixed Models with Applications in Agriculture and Biology by Josafhat Salinas Ruíz , Osval Antonio Montesinos López , Gabriela Hernández Ramírez , Jose Crossa Hiriart
English | PDF EPUB (True) | 2023 | 434 Pages | ISBN : 3031327993 | 25 MB
This book offers an introduction to mixed generalized linear models with applications to the biological sciences, basically approached from an applications perspective, without neglecting the rigor of the theory. For this reason, the theory that supports each of the studied methods is addressed and later - through examples - its application is illustrated. In addition, some of the assumptions and shortcomings of linear statistical models in general are also discussed.
Semiparametric Regression with R (Repost)
Date: 7 Apr 2023 20:53:35
Semiparametric Regression with R by Jaroslaw Harezlak
English | PDF,EPUB | 2018 | 344 Pages | ISBN : 1493988514 | 99.3 MB
This easy-to-follow applied book on semiparametric regression methods using R is intended to close the gap between the available methodology and its use in practice. Semiparametric regression has a large literature but much of it is geared towards data analysts who have advanced knowledge of statistical methods. While R now has a great deal of semiparametric regression functionality, many of these developments have not trickled down to rank-and-file statistical analysts.
Alternative Methods of Regression
Date: 6 Mar 2023 04:19:43
Alternative Methods of Regression by David Birkes, Yadolah Dodge
English | PDF | 1993 | 236 Pages | ISBN : 0471568813 | 10.5 MB
Of related interest. Nonlinear Regression Analysis and its Applications Douglas M. Bates and Donald G. Watts ".an extraordinary presentation of concepts and methods concerning the use and analysis of nonlinear regression models.highly recommend[ed].for anyone needing to use and/or understand issues concerning the analysis of nonlinear regression models." –Technometrics This book provides a balance between theory and practice supported by extensive displays of instructive geometrical constructs.
Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning
Date: 17 Feb 2023 01:36:54
Kernel Based Algorithms for Mining Huge Data Sets: Supervised, Semi-supervised, and Unsupervised Learning by Te-Ming Huang , Vojislav Kecman , Ivica Kopriva
English | PDF(True) | 2006 | 266 Pages | ISBN : 3540316817 | 5.2 MB
"Kernel Based Algorithms for Mining Huge Data Sets" is the first book treating the fields of supervised, semi-supervised and unsupervised machine learning collectively. The book presents both the theory and the algorithms for mining huge data sets by using support vector machines (SVMs) in an iterative way. It demonstrates how kernel based SVMs can be used for dimensionality reduction (feature elimination) and shows the similarities and differences between the two most popular unsupervised techniques, the principal component analysis (PCA) and the independent component analysis (ICA). The book presents various examples, software, algorithmic solutions enabling the reader to develop their own codes for solving the problems.
Methods and Applications of Linear Models: Regression and the Analysis of Variance
Date: 17 Oct 2022 19:33:29
Methods and Applications of Linear Models: Regression and the Analysis of Variance by Ronald R. Hocking
English | PDF | 2003 | 752 Pages | ISBN : 047123222X | 44 MB
A popular statistical text now updated and better than ever!
The ready availability of high-speed computers and statistical software encourages the analysis of ever larger and more complex problems while at the same time increasing the likelihood of improper usage. That is why it is increasingly important to educate end users in the correct interpretation of the methodologies involved. Now in its second edition, Methods and Applications of Linear Models: Regression and the Analysis of Variance seeks to more effectively address the analysis of such models through several important changes. Notable in this new edition:
Smoothing and Regression: Approaches, Computation, and Application
Date: 17 Oct 2022 17:56:43
Smoothing and Regression: Approaches, Computation, and Application by Michael G. Schimek
English | PDF | 2000 | 635 Pages | ISBN : 0471179469 | 44.4 MB
A comprehensive introduction to a wide variety of univariate and multivariate smoothing techniques for regression
Smoothing and Regression: Approaches, Computation, and Application bridges the many gaps that exist among competing univariate and multivariate smoothing techniques. It introduces, describes, and in some cases compares a large number of the latest and most advanced techniques for regression modeling. Unlike many other volumes on this topic, which are highly technical and specialized, this book discusses all methods in light of both computational efficiency and their applicability for real data analysis.
Nonlinear Regression
Date: 9 Oct 2022 17:06:18
Nonlinear Regression by G. A. F. Seber, C. J. Wild
English | PDF | 1989 | 782 Pages | ISBN : 0471617601 | 64.3 MB
"Nonlinear Regression also includes a reference list of over 700 entries. The compilation of this material and cross-referencing of it is one of the most valuable aspects of the book. Nonlinear Regression can provide the researcher unfamiliar with a particular specialty area of nonlinear regression an introduction to that area of nonlinear regression and access to the appropriate references . . . Nonlinear Regression provides by far the broadest discussion of nonlinear regression models currently available and will be a valuable addition to the library of anyone interested in understanding and using such models including the statistical researcher."
–Mathematical Reviews
Linear Regression Analysis, Second Edition
Date: 9 Oct 2022 16:57:02
Linear Regression Analysis, Second Edition by George A. F. Seber, Alan J. Lee
English | PDF | 2003 | 572 Pages | ISBN : 0471415405 | 9.9 MB
Concise, mathematically clear, and comprehensive treatment of the subject.
* Expanded coverage of diagnostics and methods of model fitting.
* Requires no specialized knowledge beyond a good grasp of matrix algebra and some acquaintance with straight-line regression and simple analysis of variance models.
* More than 200 problems throughout the book plus outline solutions for the exercises.
Semiparametric Regression with R (Repost)
Date: 19 Aug 2022 07:05:26
Semiparametric Regression with R by Jaroslaw Harezlak
English | PDF,EPUB | 2018 | 344 Pages | ISBN : 1493988514 | 99.3 MB
This easy-to-follow applied book on semiparametric regression methods using R is intended to close the gap between the available methodology and its use in practice. Semiparametric regression has a large literature but much of it is geared towards data analysts who have advanced knowledge of statistical methods. While R now has a great deal of semiparametric regression functionality, many of these developments have not trickled down to rank-and-file statistical analysts.
Statistical Tools for Nonlinear Regression: A Practical Guide With S-PLUS and R Examples (Repost)
Date: 30 Jul 2022 10:43:35
Statistical Tools for Nonlinear Regression: A Practical Guide With S-PLUS and R Examples by S. Huet, A. Bouvier, M. -A. Poursat, E. Jolivet
English | PDF | 2004 | 242 Pages | ISBN : 0387400818 | 3.2 MB
Statistical Tools for Nonlinear Regression, (Second Edition), presents methods for analyzing data using parametric nonlinear regression models. The new edition has been expanded to include binomial, multinomial and Poisson non-linear models. Using examples from experiments in agronomy and biochemistry, it shows how to apply these methods. It concentrates on presenting the methods in an intuitive way rather than developing the theoretical backgrounds.
"Digital Image Processing Applications" ed. by Paulo Ambrosio
Date: 2 Jul 2022 00:00:00
"Digital Image Processing Applications" ed. by Paulo Ambrosio
ITexLi | 2022 | ISBN: 1839697954 9781839697951 1839697946 9781839697944 1839697962 9781839697968 | 111 pages | PDF | 10 MB
ITexLi | 2022 | ISBN: 1839697954 9781839697951 1839697946 9781839697944 1839697962 9781839697968 | 111 pages | PDF | 10 MB
This book provides examples of digital image processing applications and presents recent research on processing concepts and techniques.
Binarization
Biology
Business
Classifications
Communication
Computer
CUDA
Detection
Digital Image Processing
DSP
Earth
Electronics
Engineering
Genetics
Hardware
Health
Mathematics
Measurements
Medicine
Models
Neurochemistry
Neuroscience
Physics
Programming
Recognition
Regression
Science
Software
Technology
Tomography
Video Coding
Essential Wavelets for Statistical Applications and Data Analysis
Date: 26 Jun 2022 17:52:56
Essential Wavelets for Statistical Applications and Data Analysis by R. Todd Ogden
English | PDF | 1997 | 218 Pages | ISBN : 0817638644 | 17.5 MB
I once heard the book by Meyer (1993) described as a "vulgarization" of wavelets. While this is true in one sense of the word, that of making a sub ject popular (Meyer's book is one of the early works written with the non specialist in mind), the implication seems to be that such an attempt some how cheapens or coarsens the subject. I have to disagree that popularity goes hand-in-hand with debasement. is certainly a beautiful theory underlying wavelet analysis, there is While there plenty of beauty left over for the applications of wavelet methods.
Chemometric Methods in Analytical Spectroscopy Technology
Date: 28 May 2022 23:10:30
Chemometric Methods in Analytical Spectroscopy Technology by Xiaoli Chu
English | EPUB | 2022 | 596 Pages | ISBN : 9811916241 | 86 MB
This book discusses chemometric methods for spectroscopy analysis including NIR, MIR, Raman, NMR, and LIBS, from the perspective of practical applied spectroscopy. It covers all aspects of chemometrics associated with analytical spectroscopy, including representative sample selection algorithm, outlier detection algorithm, model updating and maintenance algorithm and strategy and calibration performance evaluation methods.To provide a systematic and comprehensive overview the latest progress of chemometric methods including recent scientific research and practical applications are presented. In addition the book also highlights the improvement of classical algorithms and the extension of common strategies. It is therefore useful as a reference book for researchers engaged in analytical spectroscopy technology, chemometrics, analytical instruments and other related fields.