Spss Regression Models

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...

Functions for fitting least suqares regression problems under nonnegativity constraints. Optimized version of the Lawson & Hanson approach

Plot data in a figure, and then interactively choose regression area. The result from polyfit is returned.Example:x=1:1:10;y=sin(x);f=figure; plot( x,y );[p,h] = figreg( f, 2 );%fit a second order polynom to selected region in plot


Platforms: Matlab

The main advantages of the Hausdorff regression are that one should not specify the direction of the errors (vertical, horizontal, orthogonal ... with the ordinary least squares) and that it is less sensitive with respect to the square of the distance.This is the original idea. Any contribution...


Platforms: Matlab

django-typed-models provides an extra type of model inheritance for django. The concrete type of each object is stored in the database, and when the object is retrieved it is automatically cast to the correct concrete type. These are basically proxy models, but with a known type. Features ....


Platforms: *nix

I need to thank Duane Hanselman for suggesting this great idea.Fminspleas is a simple nonlinear least squares tool that fits regression models of the formY = a1*f1(X,C) + a2*f2(X,C) + ... + an*fn(X,C)X can be any array, so it works on multidimensionalproblems, and C is the set of only...


Platforms: Matlab

Kernel Regression ToolboxVersion 1.0 (R14) 01-Aug-2004General information. Comprises functions to carry out kernel regressions.General Functions: ykr - Higher order olynomial kernel regression ykr0 - 0-th order kernel regression wfunc - Exponential matrix theory kernal functions gfunc -...


Platforms: Matlab

This model simulates a CDMA2000 1xRTT Forward link (between Base Station and Mobile Station).In particular, it simulates the Radio Configuration 3 of a Forward Fundamental channel.The block CDMA2k: Initial settings allows you to set different parameters such as data rate, Power ControlSubChannel...


Platforms: Matlab

This demo implements the Active Contour Models as proposed by Kass et al.To run it with GUI 1. Type guide on the matlab prompt. 2. Click on "Go to Existing GUI" 3. Select the snk.fig file in the same directory as this file 4. Click the green arrow at the top to launch the GUI Once the GUI has...


Platforms: Matlab

bgam - Boosted Generalized Additive Models package---Implements boosting for the Generalized Additive and Linear Models (GAM and GLM).Extensible, fully documented. Implements linear and stub learners,least-squares/logistic/Poisson regression.The generalized linear model (GLM) is a flexible...


Platforms: Matlab

GMM-GMR is a set of Matlab functions to train a Gaussian Mixture Model (GMM) and retrieve generalized data through Gaussian Mixture Regression (GMR). It allows to encode efficiently any dataset in Gaussian Mixture Model (GMM) through the use of an Expectation-Maximization (EM) iterative learning...


Platforms: Matlab

In this paper i present my views on how to do systematic testing of SIMULINK models. The views present are from my own perspective based on my experience working with model based product development applications. I also provide information on some testing tools and other tips. Please let me know...


Platforms: Matlab

This function implements multivariant Gaussian kernel regression and smoothing. A few examples show how it can be used to smooth 3-d noisy images with missing data.For tutorial purpose, the function is implemented in the simplest form. Therefore, it is particularly suitable for beginners to learn...


Platforms: Matlab

This quantity measures how much the entire regression function changes when the i-th observation is deleted. Should be comparable to F_p,n-p: if the 'p-value' of D_i is 50 percent or more, then the i-th point is likely influential: investigate this point further. Cook's distance (D_i) is an...


Platforms: Matlab

Written for graduate students and researchers in the statistical and social sciences, this book describes a coherent framework for understanding binary and ordinal regression models, item response models, graded response models, and ROC analyses, and for exposing the close connection between...


Platforms: Matlab

ECR is a new method for regression analysis, which employs a supervising alpha to supervise the X-matrix decomposition. When alpha=0, ECR coincides with principal component regression (PCR), when alpha=1, ECR coincides with partial least squares (PLS), when alpha is between 0 and 1, ECR could...


Platforms: Matlab

This programme estimates the parameters in nonlinear mixed effects growth/degradation models by means of ML estimation. S-plus uses this same function that was established by J. Pinheiro & D. Bates.


Platforms: Matlab

This project deals with the translation of a Simulink models to SpecC specificationmodels. Matlab is one of the leading softwares in model based and algorithmic designing. SpecC (close to ANSI C) is a high level language which can be implemented on hardware usingSystem on Chip Environment(SCE)....


Platforms: Matlab

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...


Platforms: Matlab

models is a framework for mapping Python classes to semi-structured data. It is not an ORM because it does not map relational data to Python objects. Instead it helps to define a valuable subset of data in a key/value storage or a document-oriented database and allows to work with only certain...


Platforms: *nix