slice | R Documentation |
Plot slices of the synthetic log-likelihood.
slice(object, ranges, nsim, param = object@param, pairs = FALSE, draw = TRUE, trans = NULL, multicore = FALSE, ncores = detectCores() - 1, cluster = NULL, ...)
object |
|
ranges |
ranges of values along which we want the slices. If |
nsim |
Number of simulations used to evaluate the synthetic likelihood at each location. |
param |
Named vector containing the value of the ALL parameters (including the sliced one). Parameters that are not
in |
pairs |
if |
draw |
If |
trans |
Named vector or list of transformations to be applied to the parameters in |
multicore |
If |
ncores |
Number of cores to use if |
cluster |
An object of class |
... |
additional arguments to be passed to |
Either a vector or matrix of log-synthetic likelihood estimates, depending on whether length(parNames) ==
1 or 2.
These are returned invisibly.
Matteo Fasiolo <matteo.fasiolo@gmail.com>
data(ricker_sl) # Plotting slices of the logLikelihood slice(object = ricker_sl, ranges = list("logR" = seq(3.5, 3.9, by = 0.01), "logPhi" = seq(2, 2.6, by = 0.01), "logSigma" = seq(-2, -0.5, by = 0.01)), param = c(logR = 3.8, logSigma = log(0.3), logPhi = log(10)), nsim = 500) ## Not run: # Plotting a contour of the logLikelihood slice(object = ricker_sl, ranges = list("logR" = seq(3.5, 3.9, by = 0.01), "logPhi" = seq(2, 2.6, by = 0.01), "logSigma" = seq(-2, -0.5, by = 0.04)), pairs = TRUE, param = c(logR = 3.8, logSigma = log(0.3), logPhi = log(10)), nsim = 500, multicore = TRUE) ## End(Not run)
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