This function requires data to have been dumped to disk: see ?dump2dir and ?setoutput. This function computes the
Monte Carlo Average of a function where data from a run of lgcpPredict has been dumped to disk.
# S3 method for lgcpPredict
expectation(obj, fun, maxit = NULL, ...)an object of class lgcpPredict
a function accepting a single argument that returns a numeric vector, matrix or array object
Not used in ordinary circumstances. Defines subset of samples over which to compute expectation. Expectation is computed using information from iterations 1:maxit, where 1 is the first non-burn in iteration dumped to disk.
additional arguments
the expectated value of that function
A Monte Carlo Average is computed as:
$$E_{\pi(Y_{t_1:t_2}|X_{t_1:t_2})}[g(Y_{t_1:t_2})] \approx \frac1n\sum_{i=1}^n g(Y_{t_1:t_2}^{(i)})$$
where \(g\) is a function of interest, \(Y_{t_1:t_2}^{(i)}\) is the \(i\)th retained sample from the target
and \(n\) is the total number of retained iterations. For example, to compute the mean of \(Y_{t_1:t_2}\) set,
$$g(Y_{t_1:t_2}) = Y_{t_1:t_2},$$
the output from such a Monte Carlo average would be a set of \(t_2-t_1\) grids, each cell of which
being equal to the mean over all retained iterations of the algorithm (NOTE: this is just an example computation, in
practice, there is no need to compute the mean on line explicitly, as this is already done by default in lgcpPredict).