Open AccessCATDAT : A Program for Parametric and Nonparametric Categorical Data Analysis : User's Manual Version 1.0, 1998-1999 Progress Report.
Author(s) -
James T. Peterson
Publication year - 1999
Language(s) - English
Resource type - Reports
DOI - 10.2172/756625
Subject(s) - categorical variable , nonparametric statistics , computer science , data mining , binary data , parametric statistics , data science , r package , machine learning , modular design , artificial neural network , statistical model , artificial intelligence , binary number , statistics , mathematics , programming language , arithmetic
Natural resource professionals are increasingly required to develop rigorous statistical models that relate environmental data to categorical responses data. Recent advances in the statistical and computing sciences have led to the development of sophisticated methods for parametric and nonparametric analysis of data with categorical responses. The statistical software package CATDAT was designed to make some of these relatively new and powerful techniques available to scientists. The CATDAT statistical package includes 4 analytical techniques: generalized logit modeling; binary classification tree; extended K-nearest neighbor classification; and modular neural network