Principal Components

A script containing the methods used to develop a principal components analysis in MATLAB is presented. The results are analyzed and plotted in different ways in order to interpret the information. The script is presented in Spanish and English. Some datasets are attached and ready to...

Orthogonal Linear Regression in 3D-space by using Principal Components AnalysisThis is a wrapper function to some pieces of the code from the Statistics Toolbox demo titled "Fitting an Orthogonal Regression Using Principal Components...

Do principal components analysis (PCA) on real-valued data.Two methods are available: 'eig' and 'svd' which solve the problem by eigenvalue decomposition and singula value decomposition, respectively. Please note that 'svd' is running in 'economy' mode.


Platforms: Matlab

PickStock (copyright 2003, Bell Software and Services, Inc.) uses principal components analysis to search out potentially underpriced stocks by analyzing a user-supplied database of historical stock prices. The program is believed to be an implementation of what is known in the financial market...


Platforms: Windows

MPCA is a comprehensive suite of tools for doing discrete principal components analysis on data sets of size 100Mb or more. Scaling is done using sparse vectors, multi-threading, memory mapping, and other POSIX tricks. Reports, file dumping utilities and other utilities are included. The...


Platforms: *nix

It involves a mathematical procedure that transforms a number correlated variables into a smaller number of uncorrelated variables called principal components.Databes included with code. Requirements: - MATLAB 7.0.1 or higher


Platforms: Windows, Mac, *nix, Matlab, BSD Solaris

This m-file give you the Nipals algorithm to realize a Principal Components Analysis for statistical study. I realize this program specifically with an aim of analysis spectroscopic data. Use 'help' for description


Platforms: Matlab

XLSTAT is a complete analysis and statistics add-in for Excel. It has been developed since 1993. XLSTAT includes more than 240 features in general or field-specific solutions. The use of Excel as an interface makes XLSTAT a user-friendly and highly efficient statistical and multivariate data...


Platforms: Windows, Windows 8, Windows 7, Windows Server

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

This m-file deals with the principal component solution of the factor model thru the complete data matrix, the latent root criterion, and uses the varimax factor rotation. Optionally, it also gives the residual matrix, which results of the difference between the original correlation and the...


Platforms: Matlab

Canonical discriminant analysis is a dimension-reduction technique related to principal component analysis and canonical correlation called canonical discriminant analysis. It derives the canonical coefficients parallels that of one-way MANOVA and it finds linear combinations of the quantitative...


Platforms: Matlab

CurlyWhirly is a very simple Java 3D graph viewer suited for viewing any kind of data in three dimensions. This includes, but is not restricted to, output from Principal Components Analysis or Principal Coordinate Analysis. CurlyWhirly is a Java Swing application and uses the Java 3D API to...


Platforms: Mac

The name MVSP stands for Multi-Variate Statistical Package. MVSP was developed to be an inexpensive and easy to use program that performs a number of multivariate numerical analyses useful in many scientific fields. It calculates three basic types of eigenanalysis ordinations: principal...


Platforms: Windows

XLSTAT is a complete analysis and statistics add-in for MS Excel. It includes regression (linear, logistic, nonlinear), multivariate data analysis (PCA, DA, CA, MCA, MDS), correlation tests, parametric tests, non parametric tests, ANOVA, ANCOVA and much more. Complementary modules are available...


Platforms: Windows

Exercises and case studies for a rigorous approach to risk- and portfolio-management. This booklet stems from the review sessions of the six-day ARPM bootcamp.Contents include:Advanced multivariate statistics; copula-marginal decompositionAnnualization/projection (FFT, cumulants,...


Platforms: Matlab

This program replicates the theory given in paper "Multi-Factor Models of the Forward Price Curve" by CARLOS BLANCO, DAVID SORONOW & PAUL STEFISZYNRun simfwrdcurve.m first and then simfwrdcurv2.m.simfwrdcurve.m computes the volatility functions to calculate the principal components for each month...


Platforms: Matlab

The attached CSV file contains a 751 x 2 matrix, which can be read using the MATLAB "csvread" command.>>data = csvread('TW1.csv');The first column is the standardized test statistic Z, ranging from -3.9 to 3.6 in increments of 0.01. The second column is the cumulative distribution function (CDF)....


Platforms: Matlab

The purpose of Discriminant Analysis Programme (DAP) is to facilitate discrimination and classification of (to be) grouped data with robust estimation- and modeled structures for the covariances in a one-go software. The robust estimation methods are the S-estimator and Donoho-Stahel estimator....


Platforms: Matlab

PalmPrint Recognition System V1 : Discovrey The Best Accuracy Technique For Palmprint Recognition Based on EigenPalms The System Functions By Projecting Palmprint Images In a Feature Space That Spans The Significant Variations Among Known Images. The significant Features Are Known as...


Platforms: OS/2, Windows, Mac, *nix, Palm OS, DOS, Windows 8, Windows Phone, Windows 7, Windows Server, iOS, Symbian, Pocket PC, OpenVMS, Handheld, Other,iPod,iTouch,Palm,Java,AS/400,RIM,Netware,BEOS

Made a PCA block (principal component analysis) within Simulink. Block calculates the principle components on any sized input matrix.Equivalent of the MATLAB PRINCOMP command (currently only outputs PC).


Platforms: Matlab