anova.modelFrame | R Documentation |
Models in modelFrame
lists are compared with
anova.lme
method.
## S3 method for class 'modelFrame' anova(object, ..., test, type, adjustSigma, Terms, L, verbose)
object |
an object inheriting from class "modelFrame". |
... |
other optional fitted model objects inheriting from
classes "modelFrame", "lme", "lm", among other (see
|
test |
optional character string specifying the type of sum of
squares to be used in F-tests for the terms in the model
(see |
type |
optional character string specifying the type of sum
of squares to be used in F-tests for the terms in the
model (see |
adjustSigma |
If TRUE and the estimation method used to obtain
object was maximum likelihood, the residual
standard error is multiplied by sqrt(nobs/(nobs -
npar)), converting it to a REML-like estimate (see
|
Terms |
optional integer or character vector specifying which
terms in the model should be jointly tested to be zero
using a Wald F-test (see |
L |
optional numeric vector or array specifying linear
combinations of the coefficients in the model that should be
tested to be zero (see |
verbose |
optional logical value. If TRUE, the calling
sequences for each fitted model object are printed with
the rest of the output, being omitted if verbose =
FALSE (see |
data frame inheriting from class "anova.lme".
Wilson Lara <wilarhen@gmail.com>, Felipe Bravo <fbravo@pvs.uva.es>
Lara W., F. Bravo, D. Maguire. 2013. Modeling patterns between drought and tree biomass growth from dendrochronological data: A multilevel approach. Agric. For. Meteorol., 178-179:140-151.
##TRW chronology (mm) and inside-bark radii data(Pchron,envir = environment()) ## Parameters of allometric model to compute Diameter at Breast ## Height over bark (DBH, cm) from diameter inside bark (dib, cm) ## and Total Tree Biomass (TTB, kg tree -1 ) from DBH (Lara ## et. al. 2013): biom_param <- c(2.87, 0.85, 0.05, 2.5) ## Modeling tree-biomass fluctuations while accounting for ## within-plot source variability (see defaults in "modelFrame" ## function) trwf <- modelFrame(Pchron, to = 'cm', MoreArgs = list(mp = c(2,1, biom_param)), log.t = FALSE, on.time = FALSE) ## Fitting a single linear regression of the "tdForm" formula ## without random effects to the tree-biomass data: trwfl <- lm(log(x) ~ log(csx) + year, data = trwf$'model'$'data') ## Comparing model likelihoods with anova method: anova(trwf, trwfl)
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