Computational Statistics Handbook with MATLAB
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Table of contents:Introduction. Probability Concepts. Sampling Concepts. Generating Random Variables. Exploratory Data Analysis. Monte Carlo Methods for Inferential Statistics. Data Partitioning. Probability Density Estimation. Statistical Pattern Recognition. Nonparametric Regression. Markov Chain Monte Carlo Methods. Spatial Statistics. Appendices.Focusing on the computational aspects of statistics rather than the theoretical, this handbook uses a down-to-earth approach that makes statistics accessible to a wide range of users. The authors include algorithmic descriptions and MATLAB code for...
Table of contents:
Introduction. Probability Concepts. Sampling Concepts. Generating Random Variables. Exploratory Data Analysis. Monte Carlo Methods for Inferential Statistics. Data Partitioning. Probability Density Estimation. Statistical Pattern Recognition. Nonparametric Regression. Markov Chain Monte Carlo Methods. Spatial Statistics. Appendices.
Focusing on the computational aspects of statistics rather than the theoretical, this handbook uses a down-to-earth approach that makes statistics accessible to a wide range of users. The authors include algorithmic descriptions and MATLAB code for many of the latest methods in computational statistics. Detailed procedures are also included for readers who do not know MATLAB so they can implement the algorithms using other software packages. As a companion to the handbook, MATLAB functions are available for download that implement the techniques described in the text. This is the first book on the market to show how to use MATLAB to execute a wide variety of computational statistics methods and techniques.
Introduction. Probability Concepts. Sampling Concepts. Generating Random Variables. Exploratory Data Analysis. Monte Carlo Methods for Inferential Statistics. Data Partitioning. Probability Density Estimation. Statistical Pattern Recognition. Nonparametric Regression. Markov Chain Monte Carlo Methods. Spatial Statistics. Appendices.
Focusing on the computational aspects of statistics rather than the theoretical, this handbook uses a down-to-earth approach that makes statistics accessible to a wide range of users. The authors include algorithmic descriptions and MATLAB code for many of the latest methods in computational statistics. Detailed procedures are also included for readers who do not know MATLAB so they can implement the algorithms using other software packages. As a companion to the handbook, MATLAB functions are available for download that implement the techniques described in the text. This is the first book on the market to show how to use MATLAB to execute a wide variety of computational statistics methods and techniques.