Description Usage Arguments Value
View source: R/fitting_functions.R
The default for fit.method
is option KL
. This option uses an
objective function that minimises a discretised directed divergence from a
cumulative distribution implied by raw elicited fractiles to a normal
conditional mean prior for the linear predictor. An alterative method
moment
assigns the location parameter of the normal conditional mean
prior to the elicited median on the linear predictor scale. The variance
parameter is estimated as V = ((g(f_u) - g(f_l)/(qnorm(u) -
qnorm(l)))^2, where l is the probability associated with the fractile
f_l that defines the lower bound for the central credible interval and
u is the probability associated with the fractile f_u that
defines the upper bound for the central credible interval. This is also used
to initialise the optimisation for the KL
method. Another optimsation
method that minimises the sum of squares is also available as method
SS
. See the vignette for more details on the choice of objective
function for KL
and SS
.
1 | mV(Z, fit.method = "KL")
|
Z |
list object that contains matrix |
fit.method |
character, |
A list with vector of means m
and diagonal covariance matrix
V
.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.