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Search results for "DSTH"

PDL::IO::GD - Interface to the GD image library. River stage three • 93 direct dependents • 101 total dependents

This is the "General Interface" for the PDL::IO::GD library, and is actually several years old at this point (read: stable). If you're feeling frisky, try the new OO interface described below. The general version just provides several image IO utilit...

ETJ/PDL-2.088 - 21 Apr 2024 23:58:19 UTC - Search in distribution

Data::TreeDraw - Graphical representation of nested data structures. River stage zero No dependents

While this module was written for me to visualise the internal structure of Perl5 Objects I was developing it should serve for any data-structure where you need to quickly analyse, understand and check the internal structure and values *and* more imp...

DSTH/Data-TreeDraw-0.0.5 - 23 Jan 2010 21:27:25 UTC - Search in distribution

Statistics::PCA - A simple Perl implementation of Principal Component Analysis. River stage zero No dependents

Principal component analysis (PCA) transforms higher-dimensional data consisting of a number of possibly correlated variables into a smaller number of uncorrelated variables termed principal components (PCs). The higher the ranking of the PCs the gre...

DSTH/Statistics-PCA-0.0.1 - 07 Dec 2009 15:16:56 UTC - Search in distribution

Test::ModuleReady - Simple module for checking that a module is ready for submission. River stage zero No dependents

This module was written to help me prepare updates to modules. I have a nasty habit of over-looking tedious things like checking that the version numbers in the README, POD and $VERSION variable in the module file are all equal. Also not only checkin...

DSTH/Test-ModuleReady-v0.0.6 - 29 Jan 2010 13:47:27 UTC - Search in distribution

Statistics::FactorAnalysis - A Perl implementation of Factor Analysis using the Principal Component Method. River stage zero No dependents

Factor analysis is a statistical method by which the variability of a large set of observed variables is described in terms of a smaller set of unobserved variables termed factors. Factor analysis uses the premise that data observed from such a large...

DSTH/Statistics-FactorAnalysis-0.0-2 - 18 Dec 2009 00:38:34 UTC - Search in distribution

Statistics::MVA - Base module/Dependency for other modules in Statistics::MVA namespace. River stage one • 1 direct dependent • 1 total dependent

This module is a base module for the other modules in the Statistics::MVA namespace (e.g. Statistics::MVA::Bartlett, Statistics::MVA::Hotelling etc.). It is not intended for direct use - though it may be used for generating covariance matrices direct...

DSTH/Statistics-MVA-0.0.2 - 25 Jan 2010 19:33:27 UTC - Search in distribution

GD::Image::CopyIFS - fractal-based image copying and resizing River stage zero No dependents

This module adds to the "GD::Image" module of "GD" two methods: "copyIFS", used to copy and resize an area of one image onto another image, and "thumbIFS", used to create a rescaled image from an original. The "copyIFS" method is used analagously to ...

RKOBES/GD-Image-CopyIFS-0.25 - 19 May 2005 15:55:11 UTC - Search in distribution

Math::GSL::Linalg::SVD - Perl extension with convenience methods for performing SVD and eigenvector decomp with the gsl C libraries. River stage zero No dependents

The singular value decomposition (SVD) is an important factorization of a rectangular real matrix - see http://en.wikipedia.org/wiki/Singular_value_decomposition. Eigendecomposition is the factorization of a matrix into a canonical form, whereby the ...

DSTH/Math-GSL-Linalg-SVD-0.0.2 - 14 Dec 2009 13:38:44 UTC - Search in distribution

Algorithm::BaumWelch - Baum-Welch Algorithm for Hidden Markov Chain parameter estimation. River stage zero No dependents

The Baum-Welch algorithm is used to compute the parameters (transition and emission probabilities) of an Hidden Markov Model (HMM). The algorithm calculates the forward and backwards probabilities for each HMM state in a series and then re-estimates ...

DSTH/Algorithm-BaumWelch-v0.0.2 - 04 Feb 2010 15:34:38 UTC - Search in distribution

Algorithm::GoldenSection - Golden Section Search Algorithm for one-dimensional minimisation. River stage zero No dependents

This module is an implementation of the Golden Section Search Algorithm for finding minima of a unimodal function. In order to isolate a minimum of a univariate functions the minimum must first be isolated. Consequently the program first bounds a min...

DSTH/Algorithm-GoldenSection-0.0.2 - 14 Jan 2010 00:27:25 UTC - Search in distribution

Statistics::PCA::Varimax - A Perl implementation of Varimax rotation. River stage zero No dependents

Varimax rotation is a change of coordinates used in principal component analysis and factor analysis that maximizes the sum of the variances of the squared loadings matrix. This module exports a single routine 'rotate'. This routine is called in LIST...

DSTH/Statistics-PCA-Varimax-0.0-2 - 16 Dec 2009 16:21:41 UTC - Search in distribution

Statistics::Distributions::Ancova - Perl implementation of One-Way Analysis of Covariance for Independent Samples. River stage zero No dependents

ANCOVA is a merger of ANOVA and regression for continuous variables. As with paired t-test and repeated-measures ANOVA this test removes the obscuring effects of pre-existing individual differences among subjects and thus may increase statistical pow...

DSTH/Statistics-Distributions-Ancova-0.32.2 - 01 Dec 2009 02:59:38 UTC - Search in distribution

Statistics::MVA::BayesianDiscrimination - Two-Sample Linear Discrimination Analysis with Posterior Probability Calculation. River stage zero No dependents

Discriminant analysis is a procedure for classifying a set of observations each with k variables into predefined classes such as to allow the determination of the class of new observations based upon the values of the k variables for these new observ...

DSTH/Statistics-MVA-BayesianDiscrimination-0.0.2 - 04 Feb 2010 14:47:43 UTC - Search in distribution

Statistics::MVA::Bartlett - Multivariate Test of Equality of Population Covariance Matrices. River stage zero No dependents

Bartlett's test is used to test if k samples have equal variances. This multivariate form tests for homogeneity of the variance-covariance matrices across samples. Some statistical tests assume such homogeneity across groups or samples. This test all...

DSTH/Statistics-MVA-Bartlett-0.0.4 - 26 Jan 2010 18:51:22 UTC - Search in distribution

Statistics::Distributions::GTest - Perl implementation of the Log-Likelihood Ratio Test (G-test) of Independence. River stage zero No dependents

The G-test of independence is an alternative to the chi-square test of independence for testing for independence in contingency tables. G-tests are coming into increasing use and as with the chi-square test for independence the G-test for independenc...

DSTH/Statistics-Distributions-GTest-0.1.5 - 02 Dec 2009 15:41:23 UTC - Search in distribution

Statistics::MVA::HotellingTwoSample - Two-Sample Hotelling's T-Square Test Statistic. River stage zero No dependents

Hotelling's T-square statistics is a generalisation of Student's t statistic that is used for multivariate hypothesis testing. See http://en.wikipedia.org/wiki/Hotelling%27s_T-square_distribution....

DSTH/Statistics-MVA-HotellingTwoSample-0.0.2 - 27 Jan 2010 17:02:06 UTC - Search in distribution

Statistics::Distributions::Bartlett - Bartlett's test for equal sample variances. River stage zero No dependents

Bartlett test is used to test if k samples have equal variances. Such homogeneity is often assumed by other statistical tests and consequently the Bartlett test should be used to verify that assumption. See http://www.itl.nist.gov/div898/handbook/eda...

DSTH/Statistics-Distributions-Bartlett-0.0.2 - 27 Jan 2010 15:56:32 UTC - Search in distribution

Statistics::MVA::MultipleRegression - Simple Least Squares Linear Multiple Regression Module. River stage zero No dependents

The general purpose of multiple regression is to gain information about the relationship between several independent variables (x_i) and a dependent variable (y). The procedure involves fitting an equation of the form: y = b_o + x_1 * b_1 + x_2 * b_2...

DSTH/Statistics-MVA-MultipleRegression-0.0.1 - 21 Jan 2010 00:57:41 UTC - Search in distribution
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