Estimation theory

Outlier test on an analysis of regression based on the externally studentized residual, r-student. in matlab

The following Matlab project contains the source code and Matlab examples used for outlier test on an analysis of regression based on the externally studentized residual, r-student. . Among the considerations in the use of analysis of regression, outliers or bad values can seriously disturb the least-squares fit.

Nonlinear least square optimization through parameter estimation using the unscented kalman filter in matlab

The following Matlab project contains the source code and Matlab examples used for nonlinear least square optimization through parameter estimation using the unscented kalman filter. The Kalman filter can be interpreted as a feedback approach to minimize the least equare error.

Goodness of fit (modified) in matlab

The following Matlab project contains the source code and Matlab examples used for goodness of fit (modified).  GFIT2 Computes goodness of fit for regression model  USAGE:        [gf] = gfit2(t,y)        [gf] = gfit2(t,y,gFitMeasure)        [gf] = gfit2(t,y,gFitMeasure,options)  INPUT:            t: matrix or vector of target values for regression model            y: matrix or vector of output from regression model.

Two phase linear regression model in matlab

The following Matlab project contains the source code and Matlab examples used for two phase linear regression model.    INPUTS:        x - vector row with 'x' values        y - vector row with 'y' values        r - expected 'x'-coordinate of break point            if r is empty it is calculated during            the optimisation        p - if p is equal to 1 the fit is plotted    OUTPUT:        th - estimated paremeters of the regression            lines            y_1 = th(1) + th(2) * x            y_2 = th(3) + th(4) * x        r - the estimated break point

Linear deming regression in matlab

The following Matlab project contains the source code and Matlab examples used for linear deming regression. [ b sigma2_x x_est y_est stats] = deming(x,y,lambda,alpha) deming() performs a linear Deming regression to find the linear coefficients:                     y = b(1) + b(2)*x under the assumptions that x and y *both* contain measurement error with measurement error variance related as lambda = sigma2_y/sigma2_x (sigma2_x and sigma2_y is the measurement error variance of the x and y variables, respectively).

Theil–sen estimator in matlab

The following Matlab project contains the source code and Matlab examples used for theil–sen estimator. the Theil–Sen estimator, also known as Sen's slope estimator,slope selection,the single median method, or the Kendall robust line-fit method, is a method for robust linear regression that chooses the median slope among all lines through pairs of two-dimensional sample points.

Robust multivariate regression using the student-t distribution in matlab

The following Matlab project contains the source code and Matlab examples used for robust multivariate regression using the student-t distribution . The function mvsregress performs regression on multivariate data using the Student-t distribution. Its usage syntax is similar to that of the Statistics Toolbox function mvregress that does regression with the normal distribution. The contribution includes a user manual.

Negative binomial regression in matlab

The following Matlab project contains the source code and Matlab examples used for negative binomial regression. Performs Negative-Binomial regression. Regression coefficients are updated using IRLS, and the dispersion parameter is estimated via Chi^2 dampening. See Hardin, J.W. and Hilbe, J.M. Generalized Linear Models and Extensions. 3rd Ed. p. 251-254. for more information.

Interval prediction of a single value for a geometric mean regression-reduced major axis regression. in matlab

The following Matlab project contains the source code and Matlab examples used for interval prediction of a single value for a geometric mean regression-reduced major axis regression. . Model II regression should be used when the two variables in the regression equation are random and subject to error, i.

Window utilities in matlab

The following Matlab project contains the source code and Matlab examples used for window utilities. This zip file contains functions related to apodization and symmetric window generation: 1) atomwin - Window based on atomic functions 2) barthewin - Barcilon-Temes window 3) conneswin - Connes window 4) coshwin - Hyperbolic cosine window 5) coswin - Minimum sidelobe cosine window 6) dchebwin - Dolph-Chebyshev window 7) denkwin - Denk window 8) dslepwin - Discrete Prolate Spheroidal Sequences (DPSS) window

Pages

Subscribe to RSS - Estimation theory