categorical_bugs | R Documentation |
Bugs code for Categorical response
categorical_bugs(
nodename,
nodesCatIdx,
parentnames,
nodesintercepts,
parentcoefs
)
categorical_bugsGroup(
nodename,
nodesCatIdx,
nodesintercepts,
parentnames,
parentcoefs,
sigma,
sigma_alpha
)
nodename |
character string of response variable name. |
nodesCatIdx |
integer vector of length |
parentnames |
single character string (for one parent) or vector of characters (for multiple parent nodes) with parent node (predictor variables) names. |
nodesintercepts |
overall mean of response. Parameter from fixed-effects intercept. |
parentcoefs |
overall slope for each predictor (parent node) variable (fixed-effects). |
sigma |
within-group variance. Parameter from random-effects residual. |
sigma_alpha |
between-group variance-covariance matrix. Parameters from random-effects intercept. |
The output of fitAbn
with method = "mle"
is based on
the output of logistic regression models fit with either lm
,
glm
, glmer
, multinom
,
mblogit
or internal irls
methods.
They all use the first factor level as reference level.
Therefore, nodesCatIdx
starts with index 2
and not 1
.
nodesintercepts
and parentcoefs
refer to the values of
(Intercept)
and Estimate
of the respective model output.
Predictor names build the keys in parentcoef
.
Bugs model returned as stdout.
categorical_bugsGroup()
: Bugs code for Categorical response with varying intercept
makebugs simulateAbn
# A -> B
# Where B is a categorical variable with 4 levels.
categorical_bugs(nodename = "b",
nodesCatIdx = c(2, 3, 4),
parentnames = "a",
nodesintercepts = c(2.188650, 3.133928, 3.138531),
parentcoefs = list("a"=c(a=1.686432, a=3.134161, a=5.052104)))
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