Create a Collection of SAR Model Fits

Creates a fit collection of SAR model fits, which can then be plotted using plot.sars.

sar_multi(data, obj = c("power",
  "powerR","epm1","epm2","p1","p2","loga","koba",
  "mmf","monod","negexpo","chapman","weibull3","asymp",
  "ratio","gompertz","weibull4","betap","heleg","linear"), normaTest =
  "lillie", homoTest = "cor.fitted",verb = TRUE)

Arguments

data	A dataset in the form of a dataframe with two columns: the first with island/site areas, and the second with the species richness of each island/site.
obj	A vector of model names.
normaTest	The test used to test the normality of the residuals of each model. Can be any of "lillie" (Lilliefors Kolmogorov-Smirnov test; the default), "shapiro" (Shapiro-Wilk test of normality), "kolmo" (Kolmogorov-Smirnov test), or "none" (no residuals normality test is undertaken).
homoTest	The test used to check for homogeneity of the residuals of each model. Can be any of "cor.fitted" (a correlation of the residuals with the model fitted values; the default), "cor.area" (a correlation of the residuals with the area values), or "none" (no residuals homogeneity test is undertaken).
verb	verbose (default: verb == TRUE).

Value

A list of class 'sars' with n elements, corresponding to the n individual SAR model fits.

Details

The sar_models() function can be used to bring up a list of the 20 model names. display_sars_models() generates a table of the 20 models with model information.

Examples

data(galap)
# construct a fit_collection object of 3 SAR model fits
fit2 <- sar_multi(galap, obj = c("power", "loga", "linear"))
#> 
#>  Now attempting to fit the 3 SAR models: 
#> 
#> --  multi_sars --------------------------- multi-model SAR --
#> > power  : v
#> > loga   : v
#> > linear : v
plot(fit2)

# construct a fit_collection object of all 20 SAR model fits
fit3 <- sar_multi(galap)
#> 
#>  Now attempting to fit the 20 SAR models: 
#> 
#> --  multi_sars --------------------------- multi-model SAR --
#> > power    : v
#> > powerR   : v
#> > epm1     : v
#> > epm2     : v
#> > p1       : v
#> > p2       : v
#> > loga     : v
#> > koba     : v
#> > mmf      : v
#> > monod    : v
#> > negexpo  : v
#> > chapman  : Warning: could not compute parameters statistics
#> > weibull3 : v
#> > asymp    : v
#> > ratio    : v
#> > gompertz : v
#> > weibull4 : v
#> > betap    : v
#> > heleg    : v
#> > linear   : v