Modeling Of Pdfs Of Non-Gaussian Data, Please Log In Or Sign Up to Create a Free Account and Get Access more than 10 million Books, Magazines & Comics for FREE!, With PDF, TXT, EPUB, PDB, RTF, FB2. ONLY REGISTERED USERS can read and download the Book for FREE.
- Autor: Luping Yang
- Editor: LAP Lambert Academic Publishing
- Data de publicação: 2012-07-20
- ISBN: 3659181668
- Número de páginas: 136 pages
- Tag: modeling, gaussian
- Editor: SAS Institute
- Data de publicação: 2012-10-01
- ISBN: 1612902383
- Tag: onlinedoc, analytics, files
This DVD has been updated for the second maintenance release, SAS 9.3M2, which became available in August 2012. In previous years, products for SAS analytics software were updated only with new versions of Base SAS software, but this is no longer the case. This means that all of the core analytical SAS software products can be released to customers when enhancements are ready. To mark this newfound independence, the analytical products now have their own release-numbering scheme, beginning with 12.1. You'll find documentation for the SAS Analytics 12.1 release included in this DVD.
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- Autor: Shaila Dinkar Apte
- Editor: CRC Press
- Data de publicação: 2017-08-18
- ISBN: 1498781993
- Número de páginas: 462 pages
- Tag: random, signal, processing
This book covers random signals and random processes along with estimation of probability density function, estimation of energy spectral density and power spectral density. The properties of random processes and signal modelling are discussed with basic communication theory estimation and detection. MATLAB simulations are included for each concept with output of the program with case studies and project ideas. The chapters progressively introduce and explain the concepts of random signals and cover multiple applications for signal processing.
The book is designed to cater to a wide audience starting from the undergraduates (electronics, electrical, instrumentation, computer, and telecommunication engineering) to the researchers working in the pertinent fields.
• Aimed at random signal processing with parametric signal processing-using appropriate segment size.
• Covers speech, image, medical images, EEG and ECG signal processing.
• Reviews optimal detection and estimation.
• Discusses parametric modeling and signal processing in transform domain.
• Includes MATLAB codes and relevant exercises, case studies and solved examples including multiple choice questions
- Autor: Todd C. Headrick
- Editor: Chapman and Hall/CRC
- Data de publicação: 2009-12-08
- ISBN: 1420064908
- Número de páginas: 174 pages
- Tag: statistical, simulation, power, method, polynomials, other, transformations
Although power method polynomials based on the standard normal distributions have been used in many different contexts for the past 30 years, it was not until recently that the probability density function (pdf) and cumulative distribution function (cdf) were derived and made available. Focusing on both univariate and multivariate nonnormal data generation, Statistical Simulation: Power Method Polynomials and Other Transformations presents techniques for conducting a Monte Carlo simulation study. It shows how to use power method polynomials for simulating univariate and multivariate nonnormal distributions with specified cumulants and correlation matrices.
The book first explores the methodology underlying the power method, before demonstrating this method through examples of standard normal, logistic, and uniform power method pdfs. It also discusses methods for improving the performance of a simulation based on power method polynomials. The book then develops simulation procedures for systems of linear statistical models, intraclass correlation coefficients, and correlated continuous variates and ranks. Numerical examples and results from Monte Carlo simulations illustrate these procedures. The final chapter describes how the g-and-h and generalized lambda distribution (GLD) transformations are special applications of the more general multivariate nonnormal data generation approach. Throughout the text, the author employs Mathematica® in a range of procedures and offers the source code for download online.
Written by a longtime researcher of the power method, this book explains how to simulate nonnormal distributions via easy-to-use power method polynomials. By using the methodology and techniques developed in the text, readers can evaluate different transformations in terms of comparing percentiles, measures of central tendency, goodness-of-fit tests, and more.