Nonlinear Least Squares Fitting

GS-Calc is a spreadsheet application that will help you to organize your data, track your expenses and incomes, create reports, search and edit databases. Using fast GS-Calc pivot tables and other advanced functions you can perform the most demanding statistical calculations and data analysis....

OLS - Orthogonal Least Squares: Proposed by T. Blumensath, M. E. DaviesStOLS - Stagewise OLS: Combining StOMP ideas with OLSROLS - Regularized OLS: Combining ROMP ideas with OLS

1 Introduction PLS-DA for data analysis in chemistry and OMICS studies. Also included in this package are 3 variable selection methods: 1) target projection (TP) 2) competitive adaptive reweighted sampling (CARS) 3) subwindow permutation analysis (SPA). SPA is based on model pupulation analysis...


Platforms: Matlab

variogramfit performs a least squares fit of various theoretical variograms to an experimental, isotropic variogram. The user can choose between various bounded (e.g. spherical) and unbounded (e.g. exponential) models. A nugget variance can be modelled as well, but higher nested models are not...


Platforms: Matlab

The Bluebit .NET Matrix Library provides classes for object-oriented linear algebra in the .NET platform. It can be used to solve systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalues and eigenvectors problems, and singular value problems....


Platforms: Windows, Other

The design matrix of a GPS network is established for any kind of least squares adjustment, namely;-free (trace minimum),-minimum constrained,-over-determined.The user can adapt easily dmgps to the adjustment problem of a GPS network whose baselines are taken as observations. Moreover, it can be...


Platforms: Matlab

1 Introduction This toolbox implements all the routine PLS-related/based algorithms which kind of serves as the basics in chemometrics, including PLS calibration and prediction, leave one out cross validation (LOOCV), K-fold cross validation, Monte Carlo cross validation(MCCV), double cross...


Platforms: Matlab

Use coeffs = fit2dPolySVD(x, y, z, order) to fit a polynomial of x and y so that it provides a best fit to the data z.Uses SVD which is robust even if the data is degenerate. Will always produce a least-squares best fit to the data even if the data is overspecified or underspecified.x, y, z are...


Platforms: Matlab

The Bluebit .NET Matrix Library provides classes for object-oriented linear algebra in the .NET platform. It can be used to solve systems of simultaneous linear equations, least-squares solutions of linear systems of equations, eigenvalues and eigenvectors problems, and singular value problems....


Platforms: Windows, Other

The bootstrap is a way of estimating the variability of a statistic from a single data set by resampling it independently and with equal probabilities (Monte Carlo resampling). Allows the estimation of measures where the underlying distribution is unknown or where sample sizes are small. Their...


Platforms: Matlab

Model II regression should be used when the two variables in the regression equation are random and subject to error, i.e. not controlled by the researcher. Model I regression using ordinary least squares underestimates the slope of the linear relationship between the variables when they both...


Platforms: Matlab

Filtering of non-stationary periodic components from signals using a multi-order Vold-Kalman Filter.The Vold-Kalman Filter, introduced by HdoDEvard Vold and Jan Leuridan in 1993, is able to extract non-stationary periodic components from a signal using a known frequency vector [1]. Being...


Platforms: Matlab

Functions NELSONFUN and NELSONFIT evaluate and fit (with non-linear least-squares) the Nelson-Siegel function, a popular yield-curve approximation device.


Platforms: Matlab

Both functions caculate the Lomb normalized periodogram (aka Lomb-Scargle, Gauss-Vanicek or Least-Squares spectrum) of a vector x with coordinates in t, which is essentially a generalization of the DFT for unevenly sampled data.The codes are transcriptions from Fortran of the subroutines found in...


Platforms: Matlab

This toolbox contains a set of functions which can be used to compute the Least Median of Squares regression, the Reweighted Least Squares regression, the accociated location and scale estiamtors, and the Minimum Volume Ellipsoid. The concept is the minimization of the median of the squared...


Platforms: Matlab

Function: Savitzky-Golay Smoothing and Differentiation Filter The Savitzky-Golay smoothing/differentiation filter (i.e., the polynomial smoothing/differentiation filter, or the least-squares smoothing/differentiation filters) optimally fit a set of data points to polynomials of different degrees....


Platforms: Matlab

Implementation of Levy et al's LSCM algorithm [1]. Also includes a basic Wavefront OBJ file format reader, and an implementation taking advantage of speed-ups available using JACKET from Accelereyes to perform some computations on an NVIDIA GPU.[1] B. LdoTevy, S. Petitjean, N. Ray, and J....


Platforms: Matlab

NMath Stats is a .NET statistics library that provides functions for statistical computation and biostatistics, including descriptive statistics, probability distributions, combinatorial functions, multiple linear regression, hypothesis testing, analysis of variance, multivariate statistics,...


Platforms: Windows

We present a Matlab toolbox which can solve basic problems related to the Total Least Squares (TLS) method in the modeling. By illustrative examples we show how to use the TLS method for solution of:- linear regression model- nonlinear regression model- fitting data in 3D space- identification of...


Platforms: Matlab

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