The following Matlab project contains the source code and Matlab examples used for power and hypothesis testing for difference between two variances. . Estimates the power and the hypothesis testing for difference between two variances.

The following Matlab project contains the source code and Matlab examples used for tukey's test of additivity for a two-way classification analysis of variance. . Tukey's test of additivity for a two-way analysis of variance design with replication (can be equal or unequal sample sizes) or without replication.

The following Matlab project contains the source code and Matlab examples used for power1var. Besides the power estimation it makes the hypothesis testing concerning the one-sample variance. The function only needs the sample variance, the sample size, the hypothesized value and the significance level.

The following Matlab project contains the source code and Matlab examples used for sample size in tests for difference between two variances. . Sample size required to achieve a specified test for difference between two variances, using the normal approximation.

The following Matlab project contains the source code and Matlab examples used for single-factor analysis of variance test. . Computes the single-factor Analysis of Variance Model I or Model II for equal or unequal sample sizes.

The following Matlab project contains the source code and Matlab examples used for single-factor analysis of variance test using only means and variances. . Computes a single-factor analysis of variances test using only means and variances(without data).

The following Matlab project contains the source code and Matlab examples used for welch's test for homogeneity of variances. . Welch's test is developed to estimate whether more than two groups are homoscedastic. Also the Welch's test can be used as an alternative analysis of variance when samples variances are unequal.

The following Matlab project contains the source code and Matlab examples used for computes a two-way multivariate analysis of variance for equal or unequal sample sizes. . Computing of a two-way multivariate analysis of variance for equal or unequal sample sizes by the testing of the mean differences in several variables among several samples with two factors.

The following Matlab project contains the source code and Matlab examples used for conover's two sample squared ranks test for equality of variance. Performs the nonparametric squared ranks test on quality of variance for two samples.

The following Matlab project contains the source code and Matlab examples used for repeated measures two-way analysis of variance test. . ANOVA with two within-subject variables is used to analyze the relationship between two independent variables and the dependent variable.

The following Matlab project contains the source code and Matlab examples used for multinomial mean, variance and standard deviation. . This m-file returns the mean, variance and standard deviation of the multinomial distribution with parameters N and P.

The following Matlab project contains the source code and Matlab examples used for semi variance method and scaled windowed variance method for fractal time series analysis.. Semi variance method and scaled windowed variance method for fractal time series analysis.

The following Matlab project contains the source code and Matlab examples used for variance while using xcov xcorr. The correlation function calculated from one realization of an ensemble is inherently flawed since the expectation operation does not come into play. Hence it is important to have an idea of the variance in the correlation function.

The following Matlab project contains the source code and Matlab examples used for generate random numbers uniformally in a given range or matching a given normal distribution . randMat: Generates a matrix of random numbers with uniform or normal distribution on a specified interval [a,b] or with a specific mean (a) and variance (b) for any number of a,b pairs.

The following Matlab project contains the source code and Matlab examples used for descriptive statistic to characterize & compare data sets. . Whereas standard deviation and variance are measures of absolute variance, the coefficient of variation is a measure of relative variance.

The following Matlab project contains the source code and Matlab examples used for bootstrap homogeinity of variances test graphical approach. . The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling).

The following Matlab project contains the source code and Matlab examples used for bootstrap homogeneity of variances test t analytical approach. . The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling).

The following Matlab project contains the source code and Matlab examples used for combine variance of multiple subpopulations. This function calculates the variance of a population using only the means, variances and number of observations of its subpopulations.

The following Matlab project contains the source code and Matlab examples used for linear deming regression. [ b sigma2_x x_est y_est stats] = deming(x,y,lambda,alpha) deming() performs a linear Deming regression to find the linear coefficients:                     y = b(1) + b(2)*x under the assumptions that x and y *both* contain measurement error with measurement error variance related as lambda = sigma2_y/sigma2_x (sigma2_x and sigma2_y is the measurement error variance of the x and y variables, respectively).

The following Matlab project contains the source code and Matlab examples used for multivariate bootstrap bartlett´s test for the homogeneity of covariance matrices. . The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling).

The following Matlab project contains the source code and Matlab examples used for exponentially weighted covariance matrix. Calculates the RiskMetrics "Technical Document" (1996) exponentially weighted covariance matrix (p.179), correlation and volatilities. Input: data - needs to be in format T x k with T = # observations, k = # assets lambda = decay factor

The following Matlab project contains the source code and Matlab examples used for weighted covariance matrix. WEIGHTEDCOV returns a symmetric matrix C of weighted covariances calculated from an input T-by-N matrix Y whose rows are observations and whose columns are variables and an input T-by-1 vector w of weights for the observations.

The following Matlab project contains the source code and Matlab examples used for truncated multivariate normal.    X = rmvnrnd(MU,SIG,N,A,B) returns in N-by-P matrix X a    random sample drawn from the P-dimensional multivariate normal    distribution with mean MU and covariance SIG truncated to a    region bounded by the hyperplanes defined by the inequalities Ax<=B.

The following Matlab project contains the source code and Matlab examples used for standard deviation filter. The implemented standard deviation filter is based on calculation two integral images and subsequent common calculation of the variance by: var(X) = E[X^2] - (E[X])^2.

The following Matlab project contains the source code and Matlab examples used for reml based fitting of the linear mixed effects models with a simple variance covariance structure . HPMIXED fits the linear mixed effects models (LME models) of the form: y = X*b + Z*u + e, and with a simple variance covariance structure (VC: variance components), by solving the Henderson's mixed model equations.

The following Matlab project contains the source code and Matlab examples used for correlation elimination in multivariate correlated data . USAGE: [Y CovY] = Correlation_elimination( X ) INPUT: X denote multivariate original observations (correlated data) OUTPUT: Y denote the multivariate uncorrelated data CovY is the covariance of Y _________________________________________ Example: Transform the multivariate Poisson-Weibull (X) data to new uncorrelated data (Y) %Generating random data (using NORTA method) corrZ=[1 0.

The following Matlab project contains the source code and Matlab examples used for three-way analysis of variance with repeated measures on one factor test. . This m-file is a three-factor analysis of variance design in which there are repeated measures on only one of the factors.

The following Matlab project contains the source code and Matlab examples used for repeated measures single-factor analysis of variance test. . One-way repeated measures ANOVA is used to analyze the relationship between the independent variable and dependent variable.

The following Matlab project contains the source code and Matlab examples used for sum of conditional variance. Sum of Conditional Variance (SCV) is a new similarity metric for multi-modal image registration, eg CT-Fluoroscopy registration. This is derived using Joiint probability distribution but it is readily differentiable unline Mutual information (MI)