Bugs model for a normal distributed response variable \(X \sim \mathcal{N}(\mu,\,\sigma^{2})\).
Usage
gauss_bugs(nodename, nodesintercept, parentnames, parentcoefs, std)
gauss_bugsGroup(
nodename,
nodesintercept,
parentnames,
parentcoefs,
sigma,
sigma_alpha
)Arguments
- nodename
character string of response variable name.
- nodesintercept
overall mean of response. Parameter from fixed-effects intercept.
- parentnames
single character string (for one parent) or vector of characters (for multiple parent nodes) with parent node (predictor variables) names.
- parentcoefs
overall slope for each predictor (parent node) variable (fixed-effects).
- std
integer with standard deviation of response variable that will be converted to precision (see Details).
- sigma
within-group variance. Parameter from random-effects residual.
- sigma_alpha
between-group variance. Parameter from random-effects intercept.
Examples
gauss_bugs(nodename = "a",
parentnames = c("b", "c"),
nodesintercept = c(0.318077),
parentcoefs = list("b"=c(b=0.3059395),
"c"=c(c=0.5555)),
std = c(0.05773503))
#> a ~ dnorm(mu.a, precision.a) # Gaussian response
#> mu.a <- 0.318077 + 0.3059395*b + 0.5555*c # Linear regression
#> precision.a <- inverse(0.05773503) # precision tau = 1/standard_dev