make.set {palaeoSig} | R Documentation |
Function to simulate species data
Description
Function to simulate species data following Minchin (1987). This functions generates species response functions, simulates environmental variables and simulates species assemblages based on species response functions and environmental variables. Users can as well supply own species parameters (e.g. when simulating calibration and fossil datasets) and own environmental variables.
Usage
make.set(ndim, n, elen, emean, edistr, ecor, cnt, spec, env,...)
Arguments
ndim |
Number of environmental variables to generate. |
n |
Number of samples to be generated. |
elen |
Range of the environmental variables. Single number or vector of length ndim. |
emean |
Mean of the environmental variables. Single number or vector of length ndim. |
edistr |
Distribution of the environmental variables. Currently 'uniform' and 'Gaussian' are supported. |
ecor |
Correlation matrix of the environmental variables supplied by user. Object generated by |
cnt |
Number of counts to be simulated. |
spec |
Users may supply their own species parameters. |
env |
Users may supply their own environmental variables. |
... |
Arguments passed to |
Value
spp |
Species abundance data. |
env |
Environmental variables used to simulate species abundance data. |
spec |
Species parameters. |
Author(s)
Mathias Trachsel and Richard J. Telford
References
Minchin, P.R. (1987) Multidimensional Community Patterns: Towards a Comprehensive Model. Vegetatio, 71, 145-156.
See Also
make.env
, species
, cor.mat.fun
Examples
calib <- make.set(nspp = 90,ndim = 3,Amax = runif,fun = runif, xpar = c(-50,150),
srange = 400, alpha = 4, gamma = 4,n = 100,elen =rep(100,3),emean = rep(50,3),
edistr ='uniform', cnt = 1000)
# Provide species parameters generated above, so that the fossil data use the
# same species parameters.
fos <- make.set(ndim = 3,n = 100,elen =rep(100,3),emean = rep(50,3), edistr ='uniform',
cnt = 1000, spec = calib$spec)
# Supplying own environmental variables and species parameters.
env.vars <- make.env(100,elen =rep(100,3),emean = rep(50,3), edistr ='uniform',ndim = 3)
fos <- make.set(cnt = 1000, spec = calib$spec, env = env.vars)