

    \filetitle{assign}{Assign parameters, steady states, std deviations or cross-correlations}{model/assign}

	\paragraph{Syntax}

\begin{verbatim}
[M,Assigned] = assign(M,P)
[M,Assigned] = assign(M,Name,Value,Name,Value,...)
[M,Assigned] = assign(M,List,Values)
\end{verbatim}

\paragraph{Syntax for fast assign}

\begin{verbatim}
% Initialise
assign(M,List);

% Fast assign
M = assign(M,Values);
...
M = assign(M,Values);
...
\end{verbatim}

\paragraph{Syntax for assigning only steady-state
levels}

\begin{verbatim}
M = assign(M,'-level',...)
\end{verbatim}

\paragraph{Syntax for assignin only steady-state growth
rates}

\begin{verbatim}
M = assign(M,'-growth',...)
\end{verbatim}

\paragraph{Input arguments}

\begin{itemize}
\item
  \texttt{M} {[} model {]} - Model object.
\item
  \texttt{P} {[} struct \textbar{} model {]} - Database whose fields
  refer to parameter names, variable names, std deviations, or
  cross-correlations; or another model object.
\item
  \texttt{Name} {[} char {]} - A parameter name, variable name, std
  deviation, cross-correlation, or a regular expression that will be
  matched against model names.
\item
  \texttt{Value} {[} numeric {]} - A value (or a vector of values in
  case of multiple parameterisations) that will be assigned.
\item
  \texttt{List} {[} cellstr {]} - A list of parameter names, variable
  names, std deviations, or cross-correlations.
\item
  \texttt{Values} {[} numeric {]} - A vector of values.
\end{itemize}

\paragraph{Output arguments}

\begin{itemize}
\item
  \texttt{M} {[} model {]} - Model object with newly assigned parameters
  and/or steady states.
\item
  \texttt{Assigned} {[} cellstr \textbar{} \texttt{Inf} {]} - List of
  actually assigned parameter names, variables names (steady states),
  std deviations, and cross-correlations; \texttt{Inf} indicates that
  all values has been assigned from another model object.
\end{itemize}

\paragraph{Description}

\paragraph{Example}


