\HeaderA{ls.print}{Print `lsfit' Regression Results}{ls.print}
\keyword{regression}{ls.print}
\begin{Description}\relax
Computes basic statistics, including standard errors, t- and p-values
for the regression coefficients and prints them if \code{print.it} is
\code{TRUE}.
\end{Description}
\begin{Usage}
\begin{verbatim}
ls.print(ls.out, digits = 4, print.it = TRUE)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{ls.out}] Typically the result of \code{\LinkA{lsfit}{lsfit}()}
\item[\code{digits}] The number of significant digits used for printing
\item[\code{print.it}] a logical indicating whether the result should also be
printed
\end{ldescription}
\end{Arguments}
\begin{Value}
A list with the components
\begin{ldescription}
\item[\code{summary}] The ANOVA table of the regression
\item[\code{coef.table}] matrix with regression coefficients, standard
errors, t- and p-values
\end{ldescription}
\end{Value}
\begin{Note}\relax
Usually, you'd rather use \code{summary(lm(...))} and
\code{anova(lm(...))} for obtaining similar output.
\end{Note}
\begin{SeeAlso}\relax
\code{\LinkA{ls.diag}{ls.diag}}, \code{\LinkA{lsfit}{lsfit}}, also for examples;
\code{\LinkA{lm}{lm}}, \code{\LinkA{lm.influence}{lm.influence}} which usually are
preferable.
\end{SeeAlso}

