testrcov.asrtests {asreml3Plus} | R Documentation |
asreml
and tests whether the change
is significant.Fits a new rcov formula using asreml
and tests whether the
change is significant. If simpler = FALSE
the model to be fitted
must be more complex than the one whose fit has been stored in
asrtests.obj
. That is, the new model must have more parameters.
However, if simpler = TRUE
the model to be fitted must be simpler
than the one whose fit has been stored in asrtests.obj
in that it
must have fewer parameters. Any boundary terms are removed using
rmboundary.asrtests
, which may mean that the models are not
nested. The test is a REML likelihood ratio test that is performed using
reml.lrt.asreml
, which is only valid if the models are nested.
It compares the newly fitted model with the fit of the model in
asrtest.obj
. A row is added to the test.summary
data.frame
using the supplied label
.
testrcov.asrtests(terms=NULL, asrtests.obj, label = "R model", simpler = FALSE, alpha = 0.05, allow.unconverged = TRUE, positive.zero = FALSE, bound.test.parameters = "none", denDF="default", update = TRUE, trace = FALSE, set.terms = NULL, ignore.suffices = TRUE, constraints = "P", initial.values = NA, ...)
terms |
a model for the |
asrtests.obj |
an |
label |
a character string to use as the label in |
simpler |
a logical indicating whether the new model to be fitted is
simpler than the already fitted model whose fit is stored in
|
alpha |
the significance level for the test. |
allow.unconverged |
A |
positive.zero |
Indicates whether the hypothesized values for the
variance components being tested are on the boundary
of the parameter space. For example, this is true
for positively-constrained variance components that,
under the reduced model, are zero. This argument does
not need to be set if |
bound.test.parameters |
Indicates whether for the variance components
being tested, at least some of the hypothesized values
are on the boundary of the parameter space. The default
is |
denDF |
Specifies the method to use in computing approximate denominator
degrees of freedom when |
update |
if |
trace |
if TRUE then partial iteration details are displayed when ASReml-R functions are invoked; if FALSE then no output is displayed. |
set.terms |
a character vector specifying the terms that are to have constraints and/or initial values set prior to fitting. |
ignore.suffices |
a logical vector specifying whether the suffices of the
|
constraints |
a character vector specifying the constraints to be applied
to the terms specified in |
initial.values |
a character vector specifying the initial values for
the terms specified in |
... |
further arguments passed to |
An asrtests
object, which is a list containing:
asreml.obj
: an asreml
object containing the fit
after the term
has been omitted from the model;
wald.tab
: a 4-column data.frame
containing a
pseudo-anova table for the fixed terms produced by wald.asreml
;
test.summary
: a data.frame
with columns term
,
DF
, denDF
, p
and action
. A row is added to
it for each term
that is dropped, added or tested or a note that several terms have been
added or removed. A row contains the name of the term, the
DF, the p-value and the action taken. Possible codes are:
Dropped
, Retained
, Swapped
, Unswapped
,
Significant
, Nonsignificant
, Absent
, Added
,
Removed
and Boundary
. If the changed model did not
converge, Unconverged
will be added to the code.
Note that the logical asreml.obj$converge
also
reflects whether there is convergence.
If the term
is not in the model, then the supplied asreml
object will be returned. Also, reml.test
will have the likelihood
ratio and the p-value set to NA
and the degrees of freedom to zero.
Similarly, the row of test.summary
for the term
will have
its name, a p-value set to NA
, and action set to Absent.
asreml3Plus-package
, asrtests
, newrcov.asrtests
,
choose.model.asrtests
,
reml.lrt.asreml
, rmboundary.asrtests
,
newfit.asreml
, testswapran.asrtests
,
addrm.terms.asrtests
,
sig.devn.reparam.asrtests
## Not run: data(Wheat.dat) current.asr <- asreml(yield ~ Rep + WithinColPairs + Variety, random = ~ Row + Column + units, rcov = ~ ar1(Row):ar1(Column), data=Wheat.dat) current.asrt <- asrtests(current.asr, NULL, NULL) current.asrt <- rmboundary.asrtests(current.asrt) # Test Row autocorrelation current.asrt <- testrcov.asrtests("~ Row:ar1(Column)", current.asrt, label="Row autocorrelation", simpler=TRUE) print(current.asrt) ## End(Not run)