Description Usage Arguments Details Value Author(s) References Examples
Given an object of class synlik
this routine
provides a graphical check of whether the distribution of
the random summary statistics is multivariate normal.
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object |
An object of class |
param |
A vector of model's parameters at which the summary statistics will be simulated. |
observed |
A vector of observed summary statistics.
By default |
nsim |
number of summary statistics to be simulated
if object is of class |
cex.axis |
Axis scale expansion factor. |
cex.lab |
Axis label expansion factor. |
... |
additional arguments to be passed to
|
The method is from section 7.5 of Krzanowski (1988). The
replicate vectors of summary statistic S
are
transformed to variables which should be univariate chi
squared r.v.s with DoF given by the number of rows of
S
. An appropriate QQ-plot is produced, and the
proportion of the data differing substantially from the
ideal line is reported. Deviations at the right hand end
of the plot indicate that the tail behaviour of the
Normal approximation is poor: in the context of synthetic
likelihood this is of little consequence. Secondly,
s
is transformed to a vector which should be
i.i.d. N(0,1) under multivariate normality, and a QQ plot
is produced. Unfortunately this approach is not very
useful unless the dimension of s
is rather large.
In simulations, perfectly MVN data produce highly
variable results, so that the approach lacks any real
power.
Mainly produces plots and prints output. Also an array indicating proportion of simulated statistics smaller than observed.
Simon N. Wood, maintained by Matteo Fasiolo <matteo.fasiolo@gmail.com>.
Krzanowski, W.J. (1988) Principles of Multivariate Analysis. Oxford.
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