Least Squares Regressio Contact Php

rilt Regularized Inverse Laplace Transform [g,yfit,cfg] = rilt(t,y,s,g0,alpha) Array g(s) is the Inverse Laplace Transform of the array y(t), calculated by a regularized least squares method.This script is an emulation of S. Provencher CONTIN program, written in Fortran. See...

I have about a hundred MATLAB routines related to econometrics, statistics and introductory economics teaching, which are written mostly in my spare time in the past years. Most of these MATLAB functions / scripts are supplied with a graphic user interface so that so you may estimate the model...

This is a MATLAB(R) implementation of the ideas discussed in Lopez-Calva, G. and K. Shea, "Fitting Survival Probability Models," WILMOTT Magazine, issue 45, pp. 16-22.We estimate the parameters of three different survival probability models based on credit default swap (CDS) spreads. The...


Platforms: Matlab

Auto Gaussian & Gabor Surface fit---Functions to fit a 1D Gaussian to a curve and a 2D Gaussian or Gabor to a surface. The routines are automatic in the sense that they do not require the specification of starting guesses for the model parameters. This is done by evaluating the quality of fit for...


Platforms: Matlab

It needs a set of 3D points, equal radii constraints and orientation constraint to fit an ellipsoid into a 3D block object


Platforms: Matlab

% Based on - A simple method for fitting of bounding rectangle to closed regions - D. Chaudhuri a , A. Samal b.% fit_rectangle - Function provides a least squares fit to the% given boundary points of an object of unknown shape.%% Inputs - Boundary elements that must be a Nx2 array. (atleast 3...


Platforms: Matlab

Motofit co-refines Neutron and X-ray reflectometry data, using the Abeles matrix / Parratt recursion and least squares fitting (Genetic algorithm or Levenberg Marquardt). It works in the IGOR Pro environment (TM Wavemetrics).


Platforms: Windows, Mac, Linux

POLYFIT_ROOTS Least-squares polynomial fit to data.[R,K] = POLYFIT_ROOTS(X, Y, N, TOL) finds the roots R and constant K so that the polynomial P(s) = K*(s-R(1))*(s-R(2))* ... *(s-R(N)) is the best least-squares fit to the data Y at points X.Argument TOL bounds the accuracy of the fit, and if...


Platforms: Matlab

Add charts to your Java application or website (can be used with ASP, Php, JSP[TM] ...).RChart is a popular product due to the fact that it is very simple but powerfull and useful product.Create more than 18 different types of charts and combine them:- Linechart- Areachart- Piechart- Max.Min...


Platforms: Java

In this submission we present the code of the Replacement Method (RM) [1-4] and Enhanced Replacement Method (ERM)[5], that were proposed some time ago by our group. Both methods produce linear regression QSPR-QSAR models that are quite close the FS (full search) ones with much less computational...


Platforms: Matlab

POLYFIT3(X,Y,N,NUL,W) finds the coefficients of a polynomial P(X) of degree N that fits the data, P(X(I))~=Y(I), in a least-squares sense. Any of the coefficients can be forced to be zero, and data can be weighted.NUL is a vector with coefficients forced to be zero in usual order.W is a vector...


Platforms: Matlab

The function The LMFnlsq.m serves for finding optimal solution of an overdetermined system of nonlinear equations in the least-squares sense. The standard Levenberg- Marquardt algorithm was modified by Fletcher and coded in FORTRAN many years ago (see the Reference). This version of LMFnlsq is...


Platforms: Matlab

For a system having multiple inputs x and outputs y, the partial coherence is the coherence computed between any individual input and the output when the effect of all other inputs is removed from the output by a linear least squares prediction. This coherence obeys the usual inequality, and will...


Platforms: Matlab

DMFitter ActiveX control allows you to add sophisticated regression analysis tools to your software in a few lines of code. Features include: both linear and nonlinear (Levenberg-Marquardt) least squares curve fitting algorithms, arbitrary user models (defined analytically or by string...


Platforms: Windows

Tidal Analysis Program in PYthon (TAPPY) uses the least squares optimization function from scipy to perform a harmonic analysis (calculate amplitude and phases of a set of sine waves) of a hourly time series of water level values.


Platforms: Windows, Mac, Linux

This library implements a randomized algorithm for solving the least-squares equation x = arg min norm(A * x - b, 2) or the underdetermined system min(norm(x, 2)) s.t. Ax=b. With high probability the running this o(mn^2) for an m-by-n matrix.For details of the solver see the paper at:Blendenpik:...


Platforms: Matlab

Among the considerations in the use of analysis of regression, outliers or bad values can seriously disturb the least-squares fit. They falls far from the line implied by the rest of the data. If these points are really outliers, then the estimate of the intercept may be incorrect and the...


Platforms: Matlab

FitChiTool provides an interface similar to the Curve Fitting Toolbox to the fitChiSquare function.This allows you to perform fits using chi-square when measurement errors are known on linear or nonlinear models. It allows allows you to perform fits with multiple independent (more than one x)...


Platforms: Matlab

Two simple models are provided showing the characteristics of basic iterative algorithms for the inversion of kinematics, namely the Jacobian transpose, its pseudo-inverse and the damped least-squares (DLS). The pro's and con's can be compared interactively for a serial two-links and a...


Platforms: Matlab

The function LMFsolve.m serves for finding optimal solution of an overdetermined system of nonlinear equations in the least-squares sense. The standard Levenberg- Marquardt algorithm was modified by Fletcher and coded in FORTRAN many years ago. LMFsolve is its essentially shortened version...


Platforms: Matlab