| fitrad-class {sads} | R Documentation |
Class "fitrad" for maximum likelihood fitting of species
rank-abundance distributions
Description
This class extends mle2-class to encapsulate models of species
rank-abundance distributions
(RADs) fitted by maximum likelihood.
Objects from the Class
Objects created by a call to function fitrad, which fits
a probability distribution to an abundance vector.
Slots
rad:Object of class
"character"; root name of the species abundance distribution fitted. See man page offitradfor available models.distr:Deprecated since sads 0.2.4. See
distrfunctiontrunc:Object of class
"numeric"; truncation value used in the fitted model. 'NA' for a non-truncated distribution.rad.tab:Object of class
"rad"; rank-abundance table of observed abundances.call:Object of class
"language"; The call tomle2.call.orig:Object of class
"language"The call tomle2, saved in its original form (i.e. without data arguments evaluated).coef:Object of class
"numeric"; Vector of estimated parameters.fullcoef:Object of class
"numeric"; Fixed and estimated parameters.vcov:Object of class
"matrix"; Approximate variance-covariance matrix, based on the second derivative matrix at the MLE.min:Object of class
"numeric"; Minimum value of objective function = minimum negative log-likelihood.details:Object of class
"list"; Return value fromoptim.minuslogl:Object of class
"function"; The negative log-likelihood function.method:Object of class
"character"; The optimization method used.data:Object of class
"data.frame"; Data with which to evaluate the negative log-likelihood function.formula:Object of class
"character"; If a formula was specified, a character vector giving the formula and parameter specifications.optimizer:Object of class
"character"; The optimizing function used.
Extends
Class "mle2", directly.
Methods
- octavpred
signature(object = "fitrad", sad = "missing", rad = "missing", coef = "missing", trunc = "missing", oct = "ANY", S = "missing", N = "missing"): expected number of species per abundance octave, seeoctavandoctavpred.- plot
signature(x = "fitrad", y = "ANY"): diagnostic plots of the fitted model.- show
signature(object = "fitrad"): Displays object.- nobs
signature(object = "fitrad"): Displays number of observations (number of species) in the data to which the model was fitted.- pprad
signature(x = "fitrad", sad = "missing", coef = "missing", trunc = "missing"): plot of observed vs predicted percentiles of the abundance distribution, details inpprad.- qqrad
signature(x = "fitrad", sad = "missing", coef = "missing", trunc = "missing"): plot of observed vs predicted quantiles of the abundance distribution, details inqqrad.- radpred
signature(object = "fitrad", sad = "missing", rad = "missing", coef = "missing", trunc = "missing", distr = "missing", S = "missing", N = "missing"): expected abundances of the 1st to n-th most abundant species, seeradandradpred.
Note
Class fitrad only adds four slots to class
mle2. The descriptions of slots inherited from mle2-class
replicate those in mle2-class.
Author(s)
Paulo I Prado prado@ib.usp.br and Murilo Dantas Miranda, after Ben Bolker and R Core Team.
Source
this class builds on mle2-class of bbmle package (Bolker
2012), which in turn builds on mle-class.
References
Bolker, B. and R Development Core Team 2012. bbmle: Tools for general maximum likelihood estimation. R package version 1.0.5.2. http://CRAN.R-project.org/package=bbmle
See Also
mle2-class for all methods available from which
fitrad-class inherits; fitrad for details on
fitting RADs models; octavpred and
radpred to get rank-abundance and
frequencies of species in octaves predicted
from fitted models.
Examples
ok.gser <- fitrad(okland, "gs")
## The class has a plot method to show diagnostic plots
par(mfrow=c(2,2))
plot(ok.gser)
# The same plot, but with relative abundances
plot(ok.gser, prop = TRUE)
par(mfrow=c(1,1))
## Some useful methods inherited from mle2-class
coef(ok.gser)
confint(ok.gser)
logLik(ok.gser)
## Model selection
ok.zipf <- fitrad(okland, "zipf")
AICctab(ok.gser, ok.zipf, nobs=length(moths), base=TRUE)