An asrtests.object
that is a list
consisting of
the components asreml.obj
, wald.tab
and test.summary
.
A call to as.asrtests
with test.summary = NULL
re-initializes the
test.summary
data.frame
.
If there is no wald.tab
, wald.asreml
is called. In all cases,
recalcWaldTab
is called and any changes made as specified by the
recalcWaldTab
arguments supplied via ...
.
The label
argument can be used to include an entry in test.summary
for the starting model. If a label
is included, (i) the information criteria
calculated using the asreml.obj
will be added to the test.summary
, if
IClikelihood
is not set to none
and (ii) the number of variance
parameters is included in the denDF column, if IClikelihood
is set to none
.
as.asrtests(asreml.obj, wald.tab = NULL, test.summary = NULL,
denDF = "numeric", label = NULL,
IClikelihood = "none", bound.exclusions = c("F","B","S","C"), ...)
An object of S3-class asrtests
that also inherits S3-class list
.
an asreml
object for a fitted model.
A data.frame
containing a pseudo-anova table for
the fixed terms produced by wald.asreml
; it should have 4 or 6 columns.
Sometimes wald.asreml
returns a data.frame
and at other
times a list
. For example, it may return a list
when
denDF
is used. In this case, the Wald
component of the
list
is to be extracted and stored. It is noted that,
as of asreml version 4, wald.asreml
has a kenadj
argument.
A data.frame
with columns term
,
DF
, denDF
, p
and action
containing the
results of previous hypothesis tests.
Specifies the method to use in computing approximate denominator
degrees of freedom when wald.asreml
is called. Can be none
to suppress the computations, numeric
for numerical methods,
algebraic
for algebraic methods or default
, the default,
to automatically choose numeric or algebraic computations depending
on problem size. The denominator degrees of freedom are calculated
according to Kenward and Roger (1997) for fixed terms in the dense
part of the model.
A character
to use as an entry in the terms
column in
test.summary
to indicate as far as is possible the nature of the
model that has been fitted. The action
column in test.summary
will be Starting model
.
A character
that controls both the occurrence and the type
of likelihood for information criterion in the test.summary
of the new asrtests.object
. If none
, none are
included. Otherwise, if REML
, then the AIC and BIC based
on the Restricted Maximum Likelihood are included; if full
,
then the AIC and BIC based on the full likelihood, evaluated
using REML estimates, are included.
(See also infoCriteria.asreml
.)
A character
specifying the bound (constraint) codes that
will result in a variance parameter being excluded from the count of
estimated variance parameters in calculating information criteria.
If set to NULL
then none will be excluded.
further arguments passed to wald.asreml
and
recalcWaldTab
.
Chris Brien
Kenward, M. G., & Roger, J. H. (1997). Small sample inference for fixed effects from restricted maximum likelihood. Biometrics, 53, 983-997.
asremlPlus-package
, is.alldiffs
, as.alldiffs
,
recalcWaldTab
,
testranfix.asrtests
, chooseModel.asrtests
,
rmboundary.asrtests
,
reparamSigDevn.asrtests
if (FALSE) {
data(Wheat.dat)
# Fit initial model
current.asr <- asreml(yield ~ Rep + WithinColPairs + Variety,
random = ~ Row + Column + units,
residual = ~ ar1(Row):ar1(Column),
data=Wheat.dat)
# Load current fit into an asrtests object
current.asrt <- as.asrtests(current.asr, NULL, NULL)
# Check for and remove any boundary terms
current.asrt <- rmboundary(current.asrt)
}
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