BIOdry (version 0.9)

anova.modelFrame: Compare modelFrame objects

Description

Models in modelFrame lists are compared with anova.lme method.

Usage

# S3 method for modelFrame
anova(object, ..., test, type, adjustSigma, Terms, 
    L, verbose)

Value

data frame inheriting from class "anova.lme".

Arguments

object

an object inheriting from class "modelFrame".

...

other optional fitted model objects inheriting from classes "modelFrame", "lme", "lm", among other (see anova.lme).

test

optional character string specifying the type of sum of squares to be used in F-tests for the terms in the model (see anova.lme).

type

optional character string specifying the type of sum of squares to be used in F-tests for the terms in the model (see anova.lme).

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 anova.lme).

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 anova.lme).

L

optional numeric vector or array specifying linear combinations of the coefficients in the model that should be tested to be zero (see anova.lme).

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 anova.lme).

Author

Wilson Lara <[e-mail]>, Felipe Bravo <[e-mail]>

References

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.

Examples

##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)
 # \donttest{
 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:
 # \donttest{
 trwfl <- lm(log(x) ~ log(csx) + year,
             data = trwf$'model'$'data')
 # }
## Comparing model likelihoods with anova method:
 # \donttest{
     anova(trwf, trwfl)
 # }