

    \filetitle{chowlin}{Chow-Lin distribution of low-frequency observations over higher-frequency periods}{tseries/chowlin}

	\paragraph{Syntax}
 
 \begin{verbatim}
 [Y2,B,RHO,U1,U2] = chowlin(Y1,X2)
 [Y2,B,RHO,U1,U2] = chowlin(Y1,X2,range,...)
 \end{verbatim}
 \paragraph{Input arguments}
 
 \begin{itemize}
 \item
   \texttt{Y1} {[} tseries {]} - Low-frequency input tseries object that
   will be distributed over higher-frequency observations.
 \item
   \texttt{X2} {[} tseries {]} - Tseries object with regressors used to
   distribute the input data.
 \item
   \texttt{range} {[} numeric {]} - Low-frequency date range on which the
   distribution will be computed.
 \end{itemize}
 \paragraph{Output arguments}
 
 \begin{itemize}
 \item
   \texttt{Y2} {[} tseries {]} - Output data distributed with higher
   frequency.
 \item
   \texttt{B} {[} numeric {]} - Vector of regression coefficients.
 \item
   \texttt{RHO} {[} numeric {]} - Actually used autocorrelation
   coefficient in the residuals.
 \item
   \texttt{U1} {[} tseries {]} - Low-frequency regression residuals.
 \item
   \texttt{U2} {[} tseries {]} - Higher-frequency regression residuals.
 \end{itemize}
 \paragraph{Options}
 
 \begin{itemize}
 \item
   \texttt{'constant='} {[} \emph{\texttt{true}} \textbar{}
   \texttt{false} {]} - Include a constant term in the regression.
 \item
   \texttt{'log='} {[} \texttt{true} \textbar{} \emph{\texttt{false}} {]}
   - Logarithmise the data before distribution, de-logarithmise
   afterwards.
 \item
   \texttt{'ngrid='} {[} numeric \textbar{} \emph{\texttt{200}} {]} -
   Number of grid search points for finding autocorrelation coefficient
   for higher-frequency residuals.
 \item
   \texttt{'rho='} {[} \emph{\texttt{'estimate'}} \textbar{}
   \texttt{'positive'} \textbar{} \texttt{'negative'} \textbar{} numeric
   {]} - How to determine the autocorrelation coefficient for
   higher-frequency residuals.
 \item
   \texttt{'timeTrend='} {[} \texttt{true} \textbar{}
   \emph{\texttt{false}} {]} - Include a time trend in the regression.
 \end{itemize}
 \paragraph{Description}
 
 Chow,G.C., and A.Lin (1971). Best Linear Unbiased Interpolation,
 Distribution and Extrapolation of Time Series by Related Times Series.
 Review of Economics and Statistics, 53, pp.~372--75.
 
 See also Appendix 2 in Robertson, J.C., and E.W.Tallman (1999). Vector
 Autoregressions: Forecasting and Reality. FRB Atlanta Economic Review,
 1st Quarter 1999, pp.4--17.
 
 \paragraph{Example}


