asterdata | R Documentation |
Functions to construct and test conformance to the contract for objects
of class "asterdata"
. All other functions in this package take
model descriptions of this form.
asterdata(data, vars, pred, group, code, families, delta,
response.name = "resp", varb.name = "varb",
tolerance = 8 * .Machine$double.eps)
validasterdata(object, tolerance = 8 * .Machine$double.eps)
is.validasterdata(object, tolerance = 8 * .Machine$double.eps)
data |
a data frame containing response and predictor variables for the aster model. |
vars |
a character vector containing names of variables in the data
frame |
pred |
an integer vector satisfying |
group |
an integer vector satisfying The lines indicate a transitive relation. If there is a line from
node For example, if nodes |
code |
an integer vector satisfying all(code %in% seq(along = families) Node Note that |
families |
a list of family specifications
(see |
delta |
a numeric vector satisfying |
response.name |
a character string giving the name of the response vector. |
varb.name |
a character string giving the name of the factor covariate
that says which of the variables in the data frame |
tolerance |
numeric >= 0. Relative errors smaller
than |
object |
an object of class |
Response variables in dependence groups are taken to be in the order they appear in the response vector. The first to appear in the response vector is the first canonical statistic for the dependence group distribution, the second to appear the second canonical statistic, and so forth. The number of response variables in the dependence group must match the dimension of the dependence group distribution.
This function only handles the usual case where the subgraph for every
individual is isomorphic to subgraph for every other individual
and all initial nodes (formerly
called root nodes) correspond to the constant one. Each row of data
is the data for one individual. The vectors vars
, pred
,
group
, code
, and delta
(if not missing) describe
the subgraph for one individual (which is the same for all individuals).
In other cases for which this function does not have the flexibility to
construct the appropriate object of class "asterdata"
, such an
object will have to be constructed “by hand” using R statements
not involving this function or modifying an object produced by this
function. See the following section for description of such objects.
The functions validasterdata
and is.validasterdata
can be
used to check whether objects constructed “by hand” have been
constructed correctly.
an object of class "asterdata"
is a list containing the
following components
redata |
a data frame having |
repred |
an integer vector satisfying
Note that
|
initial |
a numeric vector specifying constants associated with
initial nodes (formerly called root nodes) of the graphical model
for all individuals. If |
regroup |
an integer vector satisfying
It also requires that the dimension of the family specified by
The lines indicate a transitive relation. If there is a line from
node For example, if nodes Note that
|
recode |
an integer vector satisfying
all(recode %in% seq(along = families) Node Note that |
families |
a copy of the argument of the same name of this function
except that any character string abbreviations are converted to objects
of class |
redelta |
a numeric vector satisfying
Note that
|
response.name |
a character string giving the name of the response
variable in |
varb.name |
a character string giving the name of the “varb”
variable in |
In addition an object of class "asterdata"
may contain (and those
constructed by this function do contain) components
pred
, group
, and code
,
which are copies of the arguments of the same names of this function.
Objects of class "asterdata"
not constructed by this function need
not contain these additional components, since they may make no sense if
the graph for all individuals is not the repetition of isomorphic subgraphs,
one for each individual.
families
and subset.asterdata
data(test1)
fred <- asterdata(test1, vars = c("m1", "n1", "n2"), pred = c(0, 1, 1),
group = c(0, 0, 2), code = c(1, 2, 2),
families = list("bernoulli", "normal.location.scale"))
is.validasterdata(fred)
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