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`

.

Embedding an R snippet on your website

Add the following code to your website.

For more information on customizing the embed code, read Embedding Snippets.