Heteroskedasticity Variance

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

Calculates the Variance Ratio Test of a time series, with or without the heteroskedasticity correction. Platforms: Matlab

>> Y = cummean(X,DIM);if X is MxN, Y is also MxN. To illustrate the functionality, lets assume X is a 1xN vector. Then, Y is a 1xN vector where the n-th entry in Y is given by mean(X(1:n)). So, Y(end) = mean(X), and Y(1) = X(1). cumvar works in the same way, and this can be done on an arbitrary... Platforms: Matlab

This function calculates the variance of a population using only the means, variances and number of observations of its subpopulations.This means you do not need to keep all individual observations in each subpopulation to later find out the variance of the pooled data. Platforms: Matlab

Computes the variance of a linear sum of variables. Requires a vector of weights (for the linear sum), and a covariance matrix of the variables. Platforms: Matlab

Moving variance v=movingvar(x,m) x is the timeseries. m is the window length. v is the variance. Aslak Grinsted 2005 Platforms: Matlab

How much in variability of some variable is contributed by variance of each shock separately.So far is for fixed number of shocks. You can change this number in the code. 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

LLR_DEMOD LLR Demodulator H = LLR_DEMOD_MEX(CONSTELLATION, MAPPING, METHOD) constructs a LLR demodulator object H for a given constellation, mapping and noise variance. The vectors CONSTELLATION and MAPPING are usually generated by using MATLAB Modem Modulation Modem. and contain the complex or... Platforms: Matlab

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. Platforms: Matlab

Suppose that you have a signal Y (Y can be a time series, a parametric surface or a volumetric data series) corrupted by a Gaussian noise with unknown variance. It is often of interest to know more about this variance. EVAR(Y) thus returns an estimated variance of the additive noise.EVAR provides... Platforms: Matlab

Semi variance method and scaled windowed variance method for fractal time series analysis.Referernce: Evaluating scaled windowed variance methods for estimating the Hurst coefficient of time series Physica A: Statistical and Theoretical PhysicsVolume 241, Issues 3-4, 15 July 1997, Pages 606-626 Platforms: Matlab

Performs the nonparametric squared ranks test on quality of variance for two samples. Based on Conover (1981), 'Practical Nonparametric Statistics', pp. 239-248.Uses normal approximation for for m >10 (MATLAB fxn norminv or table if norminv unavailable). Uses normal approximation if ties exist.... Platforms: Matlab

These files are an adaptation of the ANOVA variance component estimators to be used in the analysis of genetic data, specifically Cockerham's 1969 Theta. Formulae were adapted from Sokal and Rohlf's 1995 Biometry, and test files from the book are given as reference. Platforms: Matlab

Y = UPSIDEVARIANCE(Y) returns the upside variance for columns of variable Y.Y = UPSIDEVARIANCE(Y, m) returns the upside variance using vector m as expected value for columns of variable Y.====================================================Upside variance is defined as the average sum of squared... Platforms: Matlab

Y = DOWNSIDEVARIANCE(Y) returns the downside variance for columns of variable Y.Y = DOWNSIDEVARIANCE(Y, m) returns the downside variance using vector m as expected value for columns of variable Y.===================================================Downside variance is defined as the average sum of... Platforms: Matlab

This fuction uses the "variance ratio test" and the "rkp" associated functions to compute the variance ratio ,the tests statistics and the corresponding p-values based on randomization (simulation). Platforms: Matlab

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. Platforms: Matlab

This is a simple function that should come with the one present on this site (Variance Ratio Test) which couldn't work without this. Platforms: Matlab

This code calculates the (windowed!) running mean and variance as well asthe windowed Gaussian surprise for each newly added element.A simple (and useless) usage example: data=rand(1,100); % randomly generate 100 1-D samples history_length=10; % use a window size of 10 samples... Platforms: Matlab