Variances

The GMM returns the cluster centroid and cluster variances for a family of points if the number of clusters are predefined. The centroid and variance can then be passed to a Gaussian pdf to compute the similarity of a input query point with reference to given cluster. Platforms: Matlab

Define your database structure and relations once using the ZsqlML (Zenark's SQL Markup Language) XML DTD, and then generate mulitple vendor-specific SQL scripts, thereby solving the issue of SQL script variances across multiple platforms. Platforms: Windows, Mac, Linux

Heteroskedasticity is a sequence of random variables, that could affect statistical data if they have large variances.It will need and use the 'regstats' and 'chi2cdf' functions from the Statistics Toolbox. Requirements: - MATLAB 7.7 or higher - MATLAB's Statistics Toolbox Platforms: Windows, Mac, *nix, Matlab, BSD Solaris

In the past several years compact radio navigation receivers have proliferated in the civilian market place, generally under the name of GPS or Global Positioning System. Appearing as handheld units or built into cars, mobile phones, and airplanes, these commercial applications originated from a... Platforms: Matlab

This implementation includes modules for radiometric enhancement of colored 3D point clouds. The introduced method balances the colors of -preferably but not necessarily- overlapping point clouds in such a way that the color variances in overlapping parts of the point clouds are reduced. See... Platforms: Matlab

Analysis of Means (ANOM) is a statistical procedure for troubleshooting industrial processes and analyzing the results of experimental designs with factors at fixed levels. ANOM is an alternative to ANOVA for a fixed effects model. Unlike ANOVA only determines if there is a significant difference... Platforms: Matlab

Calculates tests of dependent and independent means, variances, correlations, proportions, alpha coefficients, and AUCs from group data. Platforms: Mac

BPSK SYSTEM SIMULATIONWe simulate the generation of random variables r0 and r1, which constitutes the input to detector. We begin by generating a binary sequence of 0?s and 1?s that occur with equal probability and are mutually (statistically) independent. For this, we use a Random number... Platforms: Matlab

variogramfit performs a least squares fit of various theoretical variograms to an experimental, isotropic variogram. The user can choose between various bounded (e.g. spherical) and unbounded (e.g. exponential) models. A nugget variance can be modelled as well, but higher nested models are not... Platforms: Matlab

This is an example of the basic Active Shape Model (ASM) and also the Active Appearance Model (AAM) as introduced by Cootes and Taylor, with multi-resolution approach, color image support and improved edge finding method. Very useful for automatic segmentation and recognition of biomedical... Platforms: Matlab

According to Wludyka and Nelson (1997), the Analysis of Means (ANOM), which is a test of location, can be converted into a test of scale and used to test the homogeneity of variances test, when the normality assumption is reasonable.The analysis of means for variances (ANOMV) is used for testing... Platforms: Matlab

Heteroskedasticity is a sequence of random variables, that could affect statistical data if they have large variances.It will need and use the 'regstats' and 'chi2cdf' functions from the Statistics Toolbox. Platforms: Matlab