Comparision of simple linear regression equations without data. As well as the before file arsos.m this procedure is suffice to test the homogeneity of k regression coefficients (Ho: b1 = b2 =...= bk). It do not needs to input data, but the sample statistics as sample size, regression coefficients, means and variances. The variability among the regression coefficients requires the F-statistic. If the null hypothesis is rejected, it can...
The Chimaera Tool Kit (CTK) is a framework for performing analysis of multiple source language projects. This includes static analysis, syntax aware searching, semantic analysis, and documentation/fact extraction. Coming soon, summer 2010.
The non-linear regression problem (univariate or multivariate) is easily posed using a graphical user interface (GUI) that solves the problem using one of the following solvers: - nlinfit: only univariate problems. - lsqnonlin: can...
Applied Analytic Systems' Multiple Linear Regression components contain all of the statistical, matrix algebra, mathematics required for modeling data from tables in which a relationship between the data in multiple datafields is suspected. The...
Orthogonal Linear Regression in 3D-space by using Principal Components Analysis
This is a wrapper function to some pieces of the code from the Statistics Toolbox demo titled "Fitting an Orthogonal Regression Using Principal...
Project:1D signal:Identification of PieceWise Linear by multiple regression
Detection of homogeneous zone using entropie Projection in the Hough space (1D) I/O
Inputs: 1D signal (xe,ye) Simulated data (Figure...
Let us suppose a set of non-linear equations in the form F(m) = d (m,d are vectors, F is a vector function of vector argument). ANNI tries to construct suitable numerical approximation for inverse projection of d to m, i.e. to find...
Measures of Analysis of Time Series (MATS) toolkit computes a number of different measures of analysis of scalar time series (linear, nonlinear and other statistical measures). It also contains pre-processing tools (transformations and...
Comparison analysis of numerical intergration methods, viz. trapezoid, Composite trapezoid, Simpson's Rule, Composite Simpson's rule, Mid-point Rule, Composite Mid-point Rule (scripts of all) taken from author's (Sulaymon L Eshkabilov) other...
Calculates slope and intercept for linear regression of data with errors in X and Y. The errors can be specified as varying point to point, as can the correlation of the errors in X and Y.
The uncertainty in the slope and intercept are...
This Recipe is a variant of recipe 576934: Numerical Inversion of the Laplace Transform using the Talbot method by Fernando Damian Nieuwveldt adapted to high precision mpmath
This code implements and plots the exact numerical solution of the Ornstein-Uhlenbeck process and its time integral. The numerical method here used was published by D.T. Gillespie in 1996 in the journal Physical Review E.
The...
Inversion of Laplace transforms is a very important procedure used in solution of complex linear systems. The function f(t)=INVLAP(F(s)) offers a simple, effective and reasonably accurate way to achieve the result. It is based on the...
Simple Zero Phase Distortion Multiplier-less Gaussian Low-Pass & High-Pass Digital Filter of a Linear Chirp.
Numerical analysis functions that employ the Bisection, Fixed-point, Newton-Raphson, and Muller's methods. Each returns a root for a given function, and optionally a iteration table.
*** Symbolic Toolbox is NOT REQUIRED ***
Stored Procedure used to determine the Linear Correlation between 2 variabes in a table of your database. This can also be used to determine the goodness of fit (Linear Regression) or best straight line between two columns of data in your...
Written for courses in numerical methods, this text introduces the use of MATLAB in numerical analysis.
It is aimed to perform comparison analysis of numerical solution search .. % methods of 2nd order ODE. Heun's Method, Euler's method, Runge-Kutta % (MATLAB built-in solver-ODE45) and analytical solution of the given ODE. % Given an...
LineFit is a port, with an additional forecast function, of the perl module Statistics::LineFit. LineFit does weighted or unweighted least-squares line fitting to two-dimensional data (y = a + b * x). (This is also called linear regression.)
This is a simple linear fem analysis of a 3D truss structure. Displacements, stress and strain are calculated.
It Can be used for any structure, you just need to have coordinates and connectivity data.
I tried to make the... |