compVagueSd: compVagueSd - Compute sD's of vague priors
In tmcd82070/evoab: Evidence of Absence (EoA)

Compute the standard deviation of a normal distribution that is big enough to be considered a 'vague' prior. This is not straight forward when there are covariates, as here.

1	compVagueSd(Y, alpha.vec, beta.vec, X, range.multiplier = 100)

`Y`	Vector of number of carcasses found, one element per year. If multiple sites are involved, elements of Y are the total (summed) number of targets found per season.
`alpha.vec`	vector of the alpha parameters of the Beta distributions
`beta.vec`	vector of the beta parameters of the Beta distributions
`X`	a design matrix upon which an approximation of inflated numbers of targets is regressed. Usually, this is meant to be the design matrix from the `eoa` function.
`range.multiplier`	a multipiler for the range of coefficient estimates to make the output standard deviations sufficiently vague. Increasing this number increases vagueness.

List containing two components. $vagueSd is a vector, one per parameter, of standard deviations that should be large enough to call vague when used in a normal prior. $startA is a vector of potential starting values for the coefficients in the model.

tmcd82070/evoab documentation built on May 13, 2020, 11:25 p.m.