# 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

# Armax garch k toolbox (estimation, forecasting, simulation and value at risk applications) in matlab

The following Matlab project contains the source code and Matlab examples used for armax garch k toolbox (estimation, forecasting, simulation and value at risk applications). ARMAX-GARCH-K Toolbox (Estimation, Forecasting, Simulation and Value-at-Risk Applications)

# 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.

# Ls & mmse channel estimators for ofdm in matlab

The following Matlab project contains the source code and Matlab examples used for ls & mmse channel estimators for ofdm. Here is a simulation based proof highlighting the superiority of the MMSE[Min Mean Sq Error] channel estimator over the LS[Least Sq] estimator.

# Arfima(p,d,q) estimator in matlab

The following Matlab project contains the source code and Matlab examples used for arfima(p,d,q) estimator. ARFIMA(p,d,q) maximum likelihood estimators: - Whittle estimator - Exact maximum likelihood estimator -and some other,possibly useful functions,forecasting included.

# Beta regression in matlab

The following Matlab project contains the source code and Matlab examples used for beta regression. Estimation of a beta regression model: Y_i ~ Beta(mu_i, mu_i * (1-mu_i) / phi), with: E(Y_i) = mu_i, Var(Y_i) = mu_i * (1-mu_i) / phi, mu_i = exp(X_i * beta)/(1 + exp(X_i * beta)). The parameters are estimated with Maximum Likelihood.
The following VB.NET project contains the source code and VB.NET examples used for Calculate Regressions for Least Squares Method. 'This program calculate Regressions for Least Squares Method Use 5 buttons for calculate: Power regression y= aX^b Exponential regression y=ae^(bx) Polynomial regression Ao +A1x + A2x^2.