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 errors (residuals) in order to achieve robustness against the outliers.
errperf(T,P,M) uses T and P, which are target and prediction vectors respectively, and returns the value for M, which is one of several error related performance metrics.
T and P can be row or column vectors of the same size. M can be...
The Toolbox forecasts the volatility of a (mxn) vector of data and from a variety of in-built / non-in-built GARCH models with various distributions, as well as the univariate RiskMetrics. The toolbox also estimates a number of Volatility Forecast...
main executing reference usage: usage_errorMeasurementsOfImages.m
The objective is to measure the differences between 2 images, and measurement of image...
This toolbox estimates the following volatility loss functions:
1. Mean Square Error, MSE
2. Mean Absolute Deviation, MAD
3. Mean Logarithm of Absolute Errors, MLAE
4. Heteroskedasticity-adjusted Mean Square Error, HMSE
Two simple functions for optimizing breakpoint placement of 1D and 2D tables.
Given an input 1D or 2D table and a desirable number of breakpoints, these functions will calculate the best placement of the breakpoints to fit the input table....
GFIT2 Computes goodness of fit for regression model
[gf] = gfit2(t,y)
[gf] = gfit2(t,y,gFitMeasure)
[gf] = gfit2(t,y,gFitMeasure,options)
t: matrix or vector of target values for...
PURE-LET has been recently proposed  as noise removal strategy from Poisson-count images. Specifically, PURE (Poisson unbiased risk estimator) is an unbiased estimate, defined in the Haar wavelet domain, of the mean-squared error between the...
Auto Gaussian & Gabor Surface fit
2 functions to fit a 2D Gaussian or 2D 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...
[lepss] = lepstest(cumclimate,xo,xf,refprob)
This code computes LEPS score
LEPS: Linear Error Probability Space (Ward and Folland, 1991)
lepss - Linear Error Probability Space Score