Nonlinear Least Squares Algorithm

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...

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...

Performs linear regression using the Least Squares method. Determines the regression coefficients, the generalized correlation coefficient and the standard error of estimate. Does multivariate regression. Displays 2D and 3D plots.


Platforms: Windows

KSudoku project can generate and solve sudoku puzzles (of different difficulty level) using a randomized least-candidate algorithm. The sudoku boards currently supported are 9x9 and 16x16: but the program is fully expandable since the algorithm is extendible to any general graph coloring...


Platforms: *nix

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

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

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

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

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

Cosinor analysis uses the least squares method to fit a sine wave to a time series. Cosinor analysis is often used in the analysis of biologic time series that demonstrate predictible rhythms. This method can be used with an unequally spaced time series. Follows cosinor analysis of a time series...


Platforms: Matlab

The zip includes:(1) lsqAffineSpace: a 'low level' routine that takes a set of m-dimensional real sample data and returns the optimal-fit k-dimensional affine subspace, with some options for discarding outliers.(2) lsqPlane and lsqLine: lsqAffineSpace wrappers, that compute optimal line and...


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

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

NMath Analysis contains classes for function minimization, root-finding, and linear programming. Product features include classes for minimizing univariate functions using golden section search and Brent's method, minimizing multivariate functions using the downhill simplex method, Powell's...


Platforms: Windows

This package is a loosely defined collection of tools for application of Python in a laboratory environment. It consists of pure python protocol drivers for various useful devices, including: National Instrument DSTP protocol to interface Python to LabVIEW VXI-11 protocol, to allow python to talk...


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

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

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

CurveFitter performs statistical regression analysis to estimate the values of parameters for linear, multivariate, polynomial, exponential and nonlinear functions. The regression analysis determines the values of the parameters that cause the function to best fit the observed data that you...


Platforms: Windows, Windows 7, Other

DataFitting is a powerful statistical analysis program that performs linear and nonlinear regression analysis (i.e. curve fitting). DataFitting determines the values of parameters for an equation, whose form you specify, that cause the equation to best fit a set of data values. DataFitting can...


Platforms: Windows, Windows 7, Other

CurveFitter program performs statistical regression analysis to estimate the values of parameters for linear, multivariate, polynomial, exponential and nonlinear functions. The regression analysis determines the values of the parameters that cause the function to best fit the observed data that...


Platforms: Windows, Other