Fit and Compare Species-Area Relationship Models Using Multimodel Inference
Fit Coleman's Random Placement Model
Use a sar_countryside() model object to predict richness
Display the model information table
Fit the General Dynamic Model of Island Biogeography
Calculate the intercepts and slopes of the different segments
Fit the log-log version of the power model
Extract Log-Likelihood for the thresholdInt class
Plot Model Fits for a 'coleman' Object
Plot Options For a 'habitat' Object
Plot Model Fits for a 'multi' Object
Plot Model Fits for a 'sars' Object
Plot Model Fits for a 'threshold' Object
Fit the Asymptotic regression model
Fit a multimodel averaged SAR curve
Fit the Beta-P cumulative model
Fit the Chapman Richards model
Fit the countryside SAR model
Fit the Extended Power model 1 model
Fit the Extended Power model 2 model
Fit the Gompertz model
Fit habitat SAR models
Fit the Heleg(Logistic) model
Fit the Kobayashi model
Fit the linear model
Fit the Logarithmic model
Fit the Logistic(Standard) model
Fit the MMF model
Fit the Monod model
Create a Collection of SAR Model Fits
Fit the Negative exponential model
Fit the Persistence function 1 model
Fit the Persistence function 2 model
Fit the Power model
Fit the PowerR model
Use SAR model fits to predict richness on islands of a given size
Fit the Rational function model
Fit threshold SAR models
Fit the Cumulative Weibull 3 par. model
Fit the Cumulative Weibull 4 par. model
Display the 21 SAR model names
sars: Fit and compare species-area relationship models using multimode...
Summarising the results of the model fitting functions
Calculate confidence intervals around breakpoints
Implements the basic elements of the multi-model inference paradigm for up to twenty species-area relationship models (SAR), using simple R list-objects and functions, as in Triantis et al. 2012 <DOI:10.1111/j.1365-2699.2011.02652.x>. The package is scalable and users can easily create their own model and data objects. Additional SAR related functions are provided.