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# RAFisher1

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Discriminant Analysis is a multivariate technique concerned with separating distinct sets of observations to previously defined groups; rather exploratory in nature, it is a separatory procedure. Here, we develop this technique considering normal populations with equal covariance matrices. So, prior to the Discriminant Analysis it performs a Multivariate Analysis of Variance to test any difference between the group's means vector. Then it describe the differential features of the observations from the known populations by trying to find discriminants whose numerical values are such that the populations are separated as much as possible.

It needs to input the multivariate data matrix, vector of prior probabilities (unknown them,pp = 1; known them,pp = 2 and [you must to give it]) and significance level (default = 0.05).

As output it gives a complete Multivariate Analysis of Variance table, mean vectors, vector of prior probabilities, testing of the Mahalanobis distances among groups, classification functions (grouping), list of misclassifications and the total percent of correct classification.

Free download from Shareware Connection - Discriminant Analysis is a multivariate technique concerned with separating distinct sets of observations to previously defined groups; rather exploratory in nature, it is a separatory procedure

Publisher: Antonio Trujillo-Ortiz | License: Shareware
Version: 1.0 | Size: 1004 KB | Platform: Matlab, Scripts
Released Date: 26-06-2013 | Rating: 0 | Title: RAFisher1

Author Url: http://www.mathworks.com
Program Info Url: http://www.mathworks.com

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anomheI - Analysis of Means (ANOM) is a statistical procedure for troubleshooting industrial processes and analyzing the results of experimental designs with factors at fixed levels

RAFisher2cda - Canonical discriminant analysis is a dimension-reduction technique related to principal component analysis and canonical correlation called canonical discriminant analysis

RAFisher1 keywords:

Homvar - Gives a menu to choose an homoscedasticity test as Bartlett, Cochran, Brown-Forsythe, Levene, O'Brien and Welch

VIDEO TUTORIAL: INPUT A MATRIX WITH EDIT TEXT - INPUT A MATRIX WITH EDIT TEXT IN A GUI (NARRATION IN SPANISH)

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Durbin - In the analysis of designed experiments, the Friedman test is the most common non-parametric test for complete block designs.

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