IRIS Toolbox Reference Manual

## regress

Ordinary or weighted least-square regression

#### Syntax

    [B,BStd,E,EStd,YFit,Range,BCov] = regress(Y,X)
    [B,BStd,E,EStd,YFit,Range,BCov] = regress(Y,X,Range,...)

#### Input arguments

- `Y` [ tseries ] - Tseries object with independent (LHS) variables.

- `X` [ tseries] - Tseries object with regressors (RHS) variables.

- `Range` [ numeric ] - Date range on which the regression will be run; if not specified, the entire range available will be used.

#### Output arguments

- `B` [ numeric ] - Vector of estimated regression coefficients.

- `BStd` [ numeric ] - Vector of std errors of the estimates.

- `E` [ tseries ] - Tseries object with the regression residuals.

- `EStd` [ numeric ] - Estimate of the std deviation of the regression residuals.

- `YFit` [ tseries ] - Tseries object with fitted LHS variables.

- `Range` [ numeric ] - The actually used date range.

- `bBCov` [ numeric ] - Covariance matrix of the coefficient estimates.

#### Options

- `'constant='` [ `true` | `false` ] - Include a constant vector in the regression; if true the constant will be placed last in the matrix of regressors.

- `'weighting='` [ tseries | empty ] - Tseries object with weights on the observations in the individual periods.

#### Description

This function calls the built-in `lscov` function.

#### Example

IRIS Toolbox. Copyright © 2007—2013 Jaromir Benes.