set_disp {bage} | R Documentation |
Specify Prior for Dispersion or Standard Deviation
Description
Specify the mean of prior for the dispersion parameter (in Poisson and binomial models) or the standard deviation parameter (in normal models.)
Usage
set_disp(mod, mean = 1)
Arguments
mod |
An object of class |
mean |
Mean value for the exponential prior.
In Poisson and binomial models, can be set to 0.
Default is |
Details
The dispersion or mean parameter has an exponential
distribution with mean \mu
,
p(\xi) = \frac{1}{\mu}\exp\left(\frac{-\xi}{\mu}\right).
By default \mu
equals 1.
In Poisson and binomial models,
mean
can be set to 0
, implying
that the dispersion term is also 0
.
In normal models, mean
must be non-negative.
If set_disp()
is applied to
a fitted model, set_disp()
unfits
the model, deleting existing estimates.
Value
A bage_mod
object
See Also
-
mod_pois()
,mod_binom()
,mod_norm()
Specify a model for rates, probabilities, or means -
set_prior()
Specify prior for a term -
set_n_draw()
Specify the number of draws -
is_fitted()
Test whether a model is fitted
Examples
mod <- mod_pois(injuries ~ age:sex + ethnicity + year,
data = nzl_injuries,
exposure = popn)
mod
mod |> set_disp(mean = 0.1)
mod |> set_disp(mean = 0)