Description Usage Arguments Value References See Also Examples
View source: R/gaussianSynLikeGhuryeOlkin.R
This function computes an unbiased, nonnegative estimate of a normal density function from simulations assumed to be drawn from it. See \insertCitePrice2018;textualBSL and \insertCiteGhurye1969;textualBSL.
1 | gaussianSynLikeGhuryeOlkin(ssy, ssx, log = TRUE, verbose = FALSE)
|
ssy |
The observed summary statisic. |
ssx |
A matrix of the simulated summary statistics. The number of rows is the same as the number of simulations per iteration. |
log |
A logical argument indicating if the log of likelihood is
given as the result. The default is |
verbose |
A logical argument indicating whether an error message
should be printed if the function fails to compute a likelihood. The
default is |
The estimated synthetic (log) likelihood value.
Other available synthetic likelihood estimators:
gaussianSynLike
for the standard synthetic likelihood
estimator, semiparaKernelEstimate
for the semi-parametric
likelihood estimator, synLikeMisspec
for the Gaussian
synthetic likelihood estimator for model misspecification.
1 2 3 4 5 6 7 8 9 | data(ma2)
ssy <- ma2_sum(ma2$data)
m <- newModel(fnSim = ma2_sim, fnSum = ma2_sum, simArgs = ma2$sim_args,
theta0 = ma2$start)
ssx <- simulation(m, n = 300, theta = c(0.6, 0.2), seed = 10)$ssx
# unbiased estimate of the Gaussian synthetic likelihood
# (the likelihood estimator used in uBSL)
gaussianSynLikeGhuryeOlkin(ssy, ssx)
|
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