manylm
is used to fit multivariate linear models
to high-dimensional data, such as multivariate abundance data in ecology.
This is the base model-fitting function - see plot.manylm
for
assumption checking, and anova.manylm
or summary.manylm
for significance testing.manylm(
formula, data=NULL, subset=NULL, weights=NULL,
na.action=options("na.action"), method="qr", model=FALSE,
x=TRUE, y=TRUE, qr=TRUE, singular.ok=TRUE, contrasts=NULL,
offset, test="LR" , cor.type= "I", shrink.param=NULL,
tol=1.0e-5, ...)
"formula"
(or one that
can be coerced to that class): a symbolic description of the
model to be fitted. The details of model specification are given
under Details.as.data.frame
to a data frame) containing
the variables in the model. If not found in data
, the
variables are taken from environment(formul
NULL
or a numeric vector.
If non-null, weighted least squares is used with weights
weights
(that is, minimizing sum(weights*e^2)
NA
s. The default is set by
the na.action
setting of options
, and is
na.fail
if that is unset. The method = "qr"
is supported; method = "model.frame"
returns
the model frame (the same as with model = TRUE
, see below).TRUE
the corresponding
components of the fit (the model frame, the model matrix, the
response, the QR decomposition) are returned.FALSE
(the default in S but
not in R) a singular fit is an error.contrasts.arg
of model.matrix.default
.NULL
or a numeric vector of
length either one or equal to the number of cases.
One or NULL
= no test
This parameter is merely stored in manylm
, and will be used as the default value of
cor.type
in subsequent functiocor.type="shrink"
. This parameter will be used as the default value of shrink.param
in subsequent functions for inference.manylm
returns an object of c("manylm", "mlm", "lm")
for multivariate
formula response and of of class c("lm")
for univariate response.
A manylm
object is a list containing at least the following components:(t(x)%*%x)
.test
argument supplied.cor.type
argument supplied.resample
argument supplied.nBoot
argument supplied.terms
object used.assign
and
(unless not requested) qr
relating to the linear
fit, for use by extractor functions such as summary.manylm
.manylm
are specified symbolically. For details on this
compare the details section of lm
and formula
. If the formula
includes an offset
, this is evaluated and subtracted from the
response.
See model.matrix
for some further details. The terms in
the formula will be re-ordered so that main effects come first,
followed by the interactions, all second-order, all third-order and so
on: to avoid this pass a terms
object as the formula (see
aov
and demo(glm.vr)
for an example).
A formula has an implied intercept term. To remove this use either
y ~ x - 1
or y ~ 0 + x
. See formula
for
more details of allowed formulae.
manylm
calls the lower level function manylm.fit
or manylm.wfit
for the actual numerical computations.
For programming only, you may consider doing likewise.
All of weights
, subset
and offset
are evaluated
in the same way as variables in formula
, that is first in
data
and then in the environment of formula
.
For details on arguments related to hypothesis testing (such as cor.type
and resample
) see summary.manylm
or
anova.manylm
.anova.manylm
, summary.manylm
, plot.manylm
data(spider)
spiddat <- log(spider$abund+1)
spiddat <- mvabund(spiddat)
X <- spider$x
lm.spider <- manylm(spiddat~X)
lm.spider
#Then use the plot function for diagnostic plots, and use anova or summary to
#evaluate significance of different model terms.
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