Creates a basic list of effects for all dependent variables in the input siena object.
getEffects(x, nintn = 10, behNintn=4, getDocumentation=FALSE)
an object of class `siena' or `sienaGroup'
Number of user-defined network interaction that can later be created.
Number of user-defined behavior interactions that can later be created.
Flag to allow documentation of internal functions, not for use by users.
An object of class sienaEffects
or sienaGroupEffects
:
this is a data frame, each part of which relates to one dependent
variable in the input object, with columns
name of the dependent variable
name of the effect
name of the function
short name for the effect
second variable to define the effect, if any
third variable to define the effect, if any
"eval", "endow", "creation", or "rate"
boolean: whether a basic rate parameter
boolean: include in the model to be fitted or not
boolean: random or fixed effect. Currently not used.
boolean: fix parameter value or not
boolean: test parameter value or not
comma separated list of periods, or "all", or ',' for none -- which time dummy interacted parameters should be included?
starting value for estimation, also used for
fix
and test
.
parameter values
"objective" or "rate"
period for basic rate parameters
"Structural", "covariate", "diffusion"
Used to store initial values which could be trimmed
Used to indicate effect number in user-specified interactions
Used to indicate effect number in user-specified interactions
Used to indicate effect number in user-specified interactions
Defines "dyadic" or "ego" or "OK" effects
here NULL, but could be replaced by a function later
here NULL, but could be replaced by a function later
Type of dependent variable: "oneMode", "behavior", or "bipartite"
name of relevant group data object
sequential number of relevant group data object in total
a unique identifier of the row
Creates a data frame of effects for use in siena model fits.
Note that the class of the return object may be lost if the data.frame
is edited using fix
.
See fix
and edit.data.frame
.
# NOT RUN {
mynet1 <- sienaDependent(array(c(s501, s502, s503), dim=c(50, 50, 3)))
mybeh <- sienaDependent(s50a, type='behavior')
mycovar <- coCovar(rnorm(50))
mydyadcovar <- coDyadCovar(matrix(as.numeric(rnorm(2500) > 2), nrow=50))
mydata <- sienaDataCreate(mynet1, mybeh, mycovar, mydyadcovar)
myeff <- getEffects(mydata)
# }
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