

    \filetitle{regress}{Ordinary or weighted least-square regression}{tseries/regress}

	\paragraph{Syntax}
 
 \begin{verbatim}
 [b,bstd,e,estd,yfit,range,bcov] = regress(y,x)
 [b,bstd,e,estd,yfit,range,bcov] = regress(y,x,range,...)
 \end{verbatim}
 \paragraph{Input arguments}
 
 \begin{itemize}
 \item
   \texttt{y} {[} tseries {]} - Tseries object with independent (LHS)
   variables.
 \item
   \texttt{x} {[} tseries{]} - Tseries object with regressors (RHS)
   variables.
 \item
   \texttt{range} {[} numeric {]} - Date range on which the regression
   will be run; if not specified, the entire range available will be
   used.
 \end{itemize}
 \paragraph{Output arguments}
 
 \begin{itemize}
 \item
   \texttt{b} {[} numeric {]} - Vector of estimated regression
   coefficients.
 \item
   \texttt{bstd} {[} numeric {]} - Vector of std errors of the estimates.
 \item
   \texttt{e} {[} tseries {]} - Tseries object with the regression
   residuals.
 \item
   \texttt{estd} {[} numeric {]} - Estimate of the std deviation of the
   regression residuals.
 \item
   \texttt{yfit} {[} tseries {]} - Tseries object with fitted LHS
   variables.
 \item
   \texttt{range} {[} numeric {]} - The actually used date range.
 \item
   \texttt{bcov} {[} numeric {]} - Covariance matrix of the coefficient
   estimates.
 \end{itemize}
 \paragraph{Options}
 
 \begin{itemize}
 \item
   \texttt{'constant='} {[} \texttt{true} \textbar{}
   \emph{\texttt{false}} {]} - Include a constant vector in the
   regression; if true the constant will be placed last in the matrix of
   regressors.
 \item
   \texttt{'weighting='} {[} tseries \textbar{} \emph{empty} {]} -
   Tseries object with weights on the observations in the individual
   periods.
 \end{itemize}
 \paragraph{Description}
 
 This function calls the built-in \texttt{lscov} function.
 
 \paragraph{Example}
 
 \}


