Spss Regression Models

The Gaussian Kernel can be changed to any desired kernel. However such a change will not dramatically improve results. This is a variant of ridge regression using the kernel trick (Mercers Theorem).

The purpose of this file is to provide beginners a way to understand and analyse time varying coefficient values within regression analysis particularly with financial data analysis.The file is easily customisable to suit requirements and contains information describing the code for ease.I am new...

Leave-one-out cross-validation for PLS regression or discriminant analysispls_cv = plscv(x,y,vl,'da')input:x (samples x descriptors) for cross-validationy (samples x variables) for regression or (samples x classes) for discriminant analysis. Classes numbers must be >0.vl (1 x 1) number of latent...


Platforms: Matlab

The animated response of several classical system models is presented. Examples include a) large amplitude pendulum motion b) falling elastic cable c) forced response of a spring-mass-damper system d) vibrating string either released with initial deflection, or shaken at one end, or subjected to...


Platforms: Matlab

This is a Wrapper (calling a simple cmd line), it includes the WEKA.jar file, the arff read and arff write files from Durga Lal Shrestha and My scripts to link them and run Model Tree, Neural Networks, support vector regression models, Linear Regression model etc, it includes a testing script...


Platforms: Matlab

This ZIP file contains function that provide simulation of the following models:- Free space loss calculation- Reflection quantization in generic surfaces for vertical and horizontal polarizations- Plane Earth loss calculations, and- Calculation of the Divergence factor in spherical Earth


Platforms: Matlab

The attached script and document help you to remove any Release 11 DSP Blockset blocks from your SimulinkdlT« models. The R11 libraries containing these blocks will no longer be shipped with Signal Processing Blocksetd-OC?D? starting with Release 2007a. If you plan to continue using these...


Platforms: Matlab

TPT offers unique and all-encompassing support for testing MATLAB/SimulinkdlT«/Stateflow- and TargetLinkdlT« models. The strengths of both systems can be used because of the perfectly tuned interface between TPT and MATLAB/Simulink. Functional models are created normally in...


Platforms: Matlab

This file includes models based on examples from the textbook, System Dynamics, 2e written by William Palm III and published by McGraw-Hill. The models are built using Simscape and Simulink. A free set of curriculum materials is available (for instructors) that includes a set of lecture slides...


Platforms: Matlab

This is the local linear version of the kernel smoothing regression function: http://www.mathworks.com/matlabcentral/fil...objectType=FILEThe local linear estimator improves the regression behaviour near the edges of the region over which the data have been collected.


Platforms: Matlab

Optimal experimental designs for generalized linear models (GLM) depend on the unknown coefficients, and two experiments having the same model but different coefficient values will typically have different optimal designs. Therefore, unlike experimental design for linear models, the prior...


Platforms: Matlab

Simulate and visualize three models for aggregated telecommunications traffic with long-range dependence: superposition of renewal processes, infinite source Poisson (M/G/Infinity) model and integrated sum of on-off processes. The simulations illustrate known limit results for the models.Under...


Platforms: Matlab

The models demonstrated here are derived from measured data corresponding to macro cellular environments with path distances ranging from 1 km to over 10 km. The Hata and Lee models are the most commonly used models for signal prediction in urban areas.FOr the analysis purpose we have also...


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 art of fitting a nonlinear regression model often starts with choosing a model form. This submission is an attempt to teach the reader a simple but general paradigm for their models as a sum of fundamental shapes that are then shifted and scaled to fit the data.I've included a bestiary of...


Platforms: Matlab

M-files for unimodality (or monotonically) constrained least squares regression.


Platforms: Matlab

Example code to accompany the "New Regression Capabilities" presentationExample code illustrating the use of the following Statistics Toolbox functionsLinearModelNonLinearModelGeneralizedLinearModel


Platforms: Matlab

This is a parallel implementation of the Expectation Maximization algorithm for multidimensional Gaussian Mixture Models, designed to run on NVidia graphics cards supportingCUDA. On my machine, it provides up to 170x performance increases (16 dims, 16 clusters, 1000000 data points).See the report...


Platforms: Matlab

Non-parametric regression is widely used in many scientific and engineering areas, such as image processing and pattern recognition.Non-parametric regression is about to estimate the conditional expectation of a random variable:E(Y|X) = f(X)where f is a non-parametric function.Based on the kernel...


Platforms: Matlab

The concept is explained in a document with a simple example. This method would be very useful for those who develop complex controller models and want to perform effective functional testing of them.


Platforms: Matlab