Multivariate Quadratic

em_ghmm : Expectation-Maximization algorithm for a HMM with Multivariate Gaussian measurement Usage ------- [logl , PI , A , M , S] = em_ghmm(Z , PI0 , A0 , M0 , S0 , [options]); Inputs ------- Z Measurements (m x K x n1 x ... x nl) PI0 Initial probabilities (d x 1) : Pr(x_1 = i) , i=1,...,d. PI0... Platforms: Matlab

% This Function solves a bilateral matrix quadratic equation% of the form AX+XB+XCX+D = 0 for X% Inputs : Matrices A,B,C, D of appropriate dimensions%% Output : The Matrix X - if a solution exists Platforms: Matlab

MVNRND2 Random vectors from the multivariate normal distribution. R = MVNRND2(MU,SIGMA,NUM) returns a NUM-by-D matrix R of multivariate normal random vectors whose mean and covariance matrix match the given input parameters, MU (1-D vector) and SIGMA (D-by-D matrix) [...] = MVNRND2(...,COVNORM)... Platforms: Matlab

Batch multivariate kernel density estimator from weighted data.The submission includes a code for estimating a multivariate bandwidth ("getBandwidth.m") matrix for a Gaussian Kernel Density Estimator. The included demonstration code ("demoBWEstimation.m") estimates a bandwidth from a weighted set... Platforms: Matlab

These are the M-files that accompany the webinar titled "New Statistics Tools in MATLAB and the Statistics Toolbox." View the recorded webinar here:http://www.mathworks.com/wbnr8328This webinar goes through 2 demos, described below:1) Analysis of survival data from motion controllers - this demo... Platforms: Matlab

The response variable is discrete ( it could be binary or multinomial), it could have "k" groups (k=2 binary, k>2 multinomial). the categorical can have "c" categories. The routine finds the weights for each category using the Fisher's method described inHubert J. Carl, Wisenbaker M. Joseph,... Platforms: Matlab

Other hypothesis used with the Mauchly's sphericity test is on the orthonormalized contrasts,H0: Cd-deOaoSC = s^2I , where C is any full-rank (p-1) x p matrix of orthonormal contrasts.A is the nonorthonormalized contrasts matrix.C = GMO(Ad-deOao) is a (p-1) doOCo p column-orthonormal matrix (by... Platforms: Matlab

This test is based on the Wilks'method (1963) designed for detection of a single outlier from a normal multivariate sample and approaching the maximun squared Mahalanobis distance to a F distribution function by the Yang and Lee (1987) formulation. A significative squared Mahalanobis distance... Platforms: Matlab

On the literature there are available several tests of the multivariate normality (ca. 50). Among them is the graphic approach based on a chi-square quantile-quantile plot of the observations' squared Mahalanobis distances. Besides the graphic q-q approaching, in this file we proposes an... 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

The function mvsregress performs multivariate Student, Cauchy and Normal regression of multivariate observations. Its usage syntax is similar to the basic syntax of the Statistics Toolbox function mvregress. The contribution includes a brief document with details of the statistical model and of... Platforms: Matlab

NDGAUSS: create ND gaussian kernel in any derivative order. g = ndgauss(hsize,sigma); [g,xi,yi,..] = ndgauss(hsize,sigma);Inputs: - hsize is N-length of kernel size. - sigma is N-length of standard deviations (gaussian widths).Outputs: - g is the kernel. The size of g is hsize(1) x hsize(2) x ...... Platforms: Matlab

This script is capable of solving a convex quadratic programming problem by Wolf's method. For the convergence of the algorithm it is necessary that either Hessian of the objective function be positive definite or positive semidefinite Hessian with linear term zero. For theory of Wolf method and... Platforms: Matlab

A control strategy for optimal operation of a hydroelectric dam is found through nonlinear and quadratic programming techniques. We use symbolic math to formulate an original model of the hydroelectric dam and then optimize the operation schedule using FMINCON. We then show how improvements can... Platforms: Matlab

Free Split and Merge Expectation-Maximization algorithm for Multivariate Gaussian Mixtures. This algorithm is suitable to estimate mixture parameters and the number of conpounds Usage ------- [logl , M , S , P] = fsmem_mvgm(Z , [M0] , [S0] , [P0] , [option]); Inputs ------- Z Measurements (d x N)... Platforms: Matlab

This software solves the economic emission dispatch by quadratic programming.The fuel cost equations,emission coefficients ,Bmn coeffcients and the demand should be entered and the subroutien emield.m should be executed. Platforms: Matlab

Generalized linear models (GLMs) are a natural extension of linear regression models in which eta = X*w is related to y by a fixed nonlinearity and a possibly non-Gaussian noise source. Standard linear regression, logistic regression and Poisson regression are all special types of GLMs.This... Platforms: Matlab

The software system allows to solve constrained nonlinear programming problems by an efficient sequential quadratic programming (SQP) method. A nonlinear objective function is to be minimized subject to nonlinear equality or inequality constraints. The numerical code is called NLPQL, which is... Platforms: Windows

RiskMetrics.m: Estimates the univariate or multivariate RiskMetrics. USAGE: rm = RiskMetrics(data,alpha) INPUTS: data = ( m x n ) vector lamba = the scale parameter method = Univariate or Multivariate OUTPUTS: rm = ( m x n ) volatility vector for the univariate case or an [( n x n )x m]... Platforms: Matlab

Software described in and associated with the paper"Numerical algorithms and issues concerning the discrete-time optimal projection equations for systems with white parameters", Proceedings UKACC International Conference on Control '98, 1-4 Sept. 1998, University of Swansea, UK, Vol. 2,... Platforms: Matlab