multiSAR: multiSAR

Description

multi-model averaging (of non-linear SAR models) and non parametric confidence intervals calculation.

Usage

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multiSAR(modelList,data,nBoot=999,crit="Info",norTest="lillie",verb=FALSE)

Arguments

modelList

Vector of character string with the names of the models to fit.

data

An mmSAR data object (a list with two elements : $name (a character sting with the name of the data set) and $data (a data.frame with 2 columns : area and richness ) ).

nBoot

The number of bootstrap resamples for the construction of the non parametric confidence interval.

crit

One of "Bayes" (for a comparison of the models based on the Bayesian Information Criterion -BIC-) or "Info" (for a comparison of the models based on the Akaike Information Criterion (AIC) -note that the function will switch automatically between AIC and it's "small sample corrected version, AICc" depending on the size of the data set- ).

norTest

The name of the test for the normality of the residuals, one of "lillie" (for a Lilliefors (Kolmogorov-Smirnov) test for the composite hypothesis of normality) or "shapiro" (for a Shapiro-Wilk test of normality).

verb

A boolean stipulating if the function should report informations while running.

Details

multiSAR is the model averaging function : fitting of SAR models is performed by calling the function rssoptim, model selection is performed using the criterion specified in argument (argument "crit"), multi-model averaging is realised for valid SAR models (see rssoptim for a description of the test performed on the fits, finally a non-parametric confidence interval is obtained using a bootstraping procedure (the argument "nBoot" give the number of bootstrap resamples, see Davison & Hinkley (1997) for an overview of bootstrap methds and their applications in regression). More details about the multimodel SAR methodology can be found in Guilhaumon et al. (2008) and the companion paper of this package (Guilhaumon et al., 2010).

Value

A list with the following elements :

References

See Also

rssoptim

Examples

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## Not run: 
#loading all available models
data(power);data(expo);data(negexpo);data(monod);data(ratio);data(logist);data(lomolino);data(weibull)

#loading the Galapagos Islands plants data set 
data(data.galap)

#creating a vector of model names
mods <- c("power","expo","negexpo","monod","logist","ratio","lomolino","weibull")

#fitting all the models to the Galapagos dataset and perform multimodel averaging
resAverage <- multiSAR(modelList=mods,data.galap)

## End(Not run)

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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