Zoning Variance

It is a statistical procedure by an analysis of variance of a latin or graeco-latin square design with or without replicates. It only needs the total sample data matrix.

Henze and Zirkler (1990) introduce a multivariate version of the univariate There are many tests for assessing the multivariate normality in the statistical literature (Mecklin and Mundfrom, 2003). Unfortunately, there is no known uniformly most powerful test and it is recommended to perform...

Functions for Rice/Rician PDF: summary statistics (mean and variance), generating random samples, and simple moment-matching to fit the distribution to data.Similar to e.g. normpdf, normstat, normrnd and normfit from the MATLAB statistics toolbox, but for the Rice distribution, which is useful in...


Platforms: Matlab

Estimates the statistical power of an analysis of variance Model II (random-effects) after it has been performed. It requires the observed F-statistic value, numerator degrees of freedom, denominator degrees of freedom and significance level.


Platforms: Matlab

This is a three-factor analysis of variance design in which all factors are within-subjects variables. In repeated measures designs, the same participants are used in all conditions. This is like an extreme matching. This allows for reduction of error variance due to subject factors. Fewer...


Platforms: Matlab

This is a three-factor analysis of variance design in which there are repeated measures on two of the factors. In repeated measures designs, the same participants are used in all conditions. This is like an extreme matching. This allows for reduction of error variance due to subject factors....


Platforms: Matlab

This m-file is used in experiments involving several factors where it is necessary to investigate the joint effects (main and interactions) of the factors on a response variable and determine by a formal analysis of variance which factor effects are nonzero. Each of the three factors (k = 3) of...


Platforms: Matlab

In a one-way analysis of variance random effects model one would expect that the measurements lie close together because the same quantity was measured and states that the class effects stem from a common source and therefore should not difer too much. In the random model some variation is...


Platforms: Matlab

The script generates spatial data with a scale-invariant power spectrum (1/f noise) and a normal error distribution.The spectral density of the data is proportional to f^BETA, where f is the frequency and BETA is the spectral exponent (BETA=0 is white noise, BETA=-2 is Brown noise).To generate...


Platforms: Matlab

Estimating of the statistical power of a performed (a posteriori) single factor Multivariate Analysis of Variance (MANOVA).It needs to input the observed parameters among two possible options. Option 1: multivariate observed F-statistic, numerator degrees of freedom, denominator degrees of...


Platforms: Matlab

Forces the pdf of data to have a normal distribution using a data adaptive lookup table. [normX,Bx,By]=normalizepdf(X)normX=N(X), where N is an data adaptive monotonically increasing function. normX will have zero mean and unit variance.Bx,By is the lookup table


Platforms: Matlab

ANOVA with between- and within- subject variables (mixed) is used to analyze the relationship for designs that have a combination of between and within-subject variables.It needs to input the X- data matrix (Size of matrix must be n-by-4;dependent variable=column 1;independent variable 1...


Platforms: Matlab

This file computes a balanced incomplete block design [BIBD] analysis of variance. A BIBD is a set X of v >= 2 elements called treatments and a collection of b > 0 subsets of X, called blocks, such that the following conditions are satisfied: - each block consists of exactly k treatments, v > k >...


Platforms: Matlab

Using the Cholesky decomposition, it generates n iterations of multivariate Gaussian random variables for a given mean vector (mu) and variance-covariance matrix (sigma).mvgrnd(mu,sigma,n)


Platforms: Matlab

This file computes the standard (simple) split-plot design analysis of variance, taking into account the linear model:x_jkl = dlTA + a_j + doDc_k + d_jk + doDT_l + (doDcdoDT)_kl + e_jklwhere j = 1,...,a (blocks); k = 1,...,b (factor 1); l = 1,...,c (factor 2); d_jk ~ N[0,var_d] (error main...


Platforms: Matlab

This file estimates the a priori statistical power of a single-factor Multivariate Analysis of Variance (MANOVA).The MATLAB macro needs to Input the R2-alternate-hypothetical population proportion of variance of the source-proportion of residual variance (error) ratio [PVs/PVe], p-number of...


Platforms: Matlab

Levene's F test is used to test the null hypothesis that multiple population variances corresponding to multiplesamples are equal. Prior to the analysis the data are transforming to the absolute deviation of the mean. Then perform an one-way analysis of variance.


Platforms: Matlab

Sample size required in tests concerning the variance, employing the Chi-square distribution and solved by iterative fashion (directed trial and error). This means that we enter an initial value for n in order to obtain a better estimate. It only needs the sample variance, expected (hypothesized)...


Platforms: Matlab

Sample size required to achieve a specified test for difference between two variances, using the normal approximation. This estimate assumes equal or unequal sample sizes. File only needs the sample size vector, variance vector, hypothesis direction, desired sample size (equal or unequal), sizes...


Platforms: Matlab

Estimates the complete table of the two level nested analysis of variance for a design with equal or unequal sample sizes (it is referred to the levels of nested factor). Please, first see the README.txt file. Main file only needs the X data matrix and indicating whether it is with equal or...


Platforms: Matlab