Multivariate

We use the power of symbolic toolbox in order to find the optimal point in an arbitrary multivariate functionChange the following code based on your objective function and run the programFunction F in Symbolic Formata='(x1^2+x2-11)^2+(x1+x2^2-7)^2';The code will iterate and converge to x and y of...

this function plots the 2D multivariate gaussian when the mean and covariance are provided. It does not use for loops. ex: plot mean=[10;11],cov=[6 0;0 6] 2D multivariate gaussian function >> mvg([10;11],[6 0;0 6])

Fit a multivariate gaussian mixture by a cross-entropy method. Cross-Entropy is a powerfull tool to achieve stochastic multi-extremum optimization.Please visit http://iew3.technion.ac.il/CE/ for more informationsi) Please compile mex-files by the mexme_ce_gauss.m (if compiler is not setup, run...


Platforms: Matlab

To walk through the code and for a thorough description, refer toA. Meucci (2009) , "Review of Statistical Arbitrage, Cointegration, and Multivariate Ornstein-Uhlenbeck",Latest version of article and code available at http://symmys.com/node/132


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

Graphical user interface driven first-order multivariate calibration using up-to-date methods, including PCR, PLS, net analyte methods and ortoghonal signal correction. Provides a variety of pre-processing tools, cross-validation plots, prediction plots, elliptical joint region plots, net analyte...


Platforms: Matlab

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

SPECTRAL_MVA is a GUI for running Multivariate analysis of spectroscopic dataInitially designed for analysis of X-ray Photoelectron spectra, can be used for analysis of any type of data tables, containing spectra or any other dataOpens MAT files with or without a variable X. Opens VMS files (XPS...


Platforms: Matlab

MVLOGNRAND MultiVariate Lognormal random numbers with correlation.This function will generate multivariate lognormal random numbers with correlation.Often one would simulation a lognormal distribution by first simulating a normal and then taking the exponent of it.If you provide the correlation...


Platforms: Matlab

This GUI includes is a set of multivariate image analysis methods for analyzing image data sets acquired at two variables. For example: emission excitation image data, spectral or dynamic (temporal) sequences of images acquired at different depths using microscopy.Two approaches are included:1....


Platforms: Matlab

MVG is a multivariate Gaussian (normal) random number generator. A user can generate a vector from the multivariate normal distribution of any dimension by specifying a mean vector and symmetric positive-definite covariance matrix. A linear transformation based on the Cholesky decomposition of...


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

tKL between two multivariate normal probability density functions. This program implements the tKL between two multivariate normal probability density functions following the references: Baba C. Vemuri, Meizhu Liu, Shun-Ichi Amari and Frank Nielsen, Total Bregman Divergence and its Applications...


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

The Unscrambler® is the complete multivariate analysis and experimental design software, equipped with powerful methods including Principal Component Analysis (PCA), Multivariate Curve Resolution (MCR), Partial Least Squares Regression (PLS-R), 3-Way PLS Regression, K-Means Clustering and SIMCA...


Platforms: Windows

exploRase was specially designed as an Open Source R-based instrument for the exploratory multivariate analysis of Systems Biology data. It provides a GUI on top of the analysis functionality provided by R and the Bioconductor project. exploRase is designed to be accessible to biologists...


Platforms: Windows

Statistics software for data analysis and multivariate statistical analysis. Probability analysis. Compute descriptive statistics of selected data. Frequency analysis. Compare means and variances. Variance analysis. Z test. Correlation tests. Jarque Bera test. Non-parametric tests, including...


Platforms: Windows, Windows 7, Windows Server

USAGE: [Y CovY] = Correlation_elimination( X )INPUT:X denote multivariate original observations (correlated data)OUTPUT:Y denote the multivariate uncorrelated dataCovY is the covariance of Y_________________________________________Example:Transform the multivariate Poisson-Weibull (X) data to new...


Platforms: Matlab

Multivariate normal simulations where sample mean and covariances match the respective population moments, refer toA. Meucci (2009), "Simulations with Exact Means and Covariances",Latest version of article and code available at http://symmys.com/node/162


Platforms: Matlab

Hotelling's T-Squared multivariate test for one sample, two independent samples [homoskedasticity or heteroskedasticity (to test)] and two dependent samples.


Platforms: Matlab