speciesModel {SiMRiv} | R Documentation |
Defines a species model to adjust to a real trajectory
Description
The sole purpose of this function is to be used in conjunction with adjustModel
. It is used to tell the optimization
algorithm which parameters are to be approximated, and which are constant.
Usage
speciesModel(type, perceptual.range = 0, steplength = 1
, prob.upperbound = 0.5, max.concentration = 0.99)
Arguments
type |
the type of movement to "fit". One of |
perceptual.range |
the perceptual range for all states. |
steplength |
the fixed step length for fixed step length types |
prob.upperbound |
the maximum allowed value for the state switching probabilities. The default is 0.5 because very high state switching probabilities don't make much sense from a biological point of view. |
max.concentration |
the maximum allowed value for the turning angle concentration parameter for CRWs [0, 1]. By default it is set to 0.99 because values higher than this (for technical reasons) result in straight line paths, which is a technical artifact. |
Details
This function defines the type of movement to be adjusted with adjustModel
. Before choosing the type, it is good practice
to plot the real trajectory and visually assess which would be the most adequate model to try. Currently included movement types are:
CRW
: single state CRW, fixed step length (1 parameter)RW.CRW
: two state RW/CRW, fixed step length (3 parameters)CRW.CRW
: two state CRW/CRW, fixed step length, (4 parameters)RW.CRW.sl
: two state RW/CRW, variable step length, (5 parameters)CRW.CRW.sl
: two state CRW/CRW, variable step length (6 parameters)CRW.CRW.CRW.sl
: three state CRW/CRW/CRW, variable step length (12 parameters)CRW.RW.Rest.sl
: three state CRW/RW/Rest, variable step length (7 parameters)
However, the user can easily write any custom function for addressing other movement types, see the code for details.
Value
Returns a function that creates a species from a vector of parameter values. This function is normally used to create species
from the adjustModel
results, see examples there.
See Also
Examples
library(SiMRiv)
model <- speciesModel("RW.CRW.sl")
# this shows the parameters that will be approximated
model
# this creates a species with 2 states
# RW and a CRW with correlation 0.9
# with the switching probabilities RW->CRW = 0.01, CRW->RW = 0.05
# and the step lengths RW = 15, CRW = 50.
species <- model(c(0.9, 0.01, 0.05, 15, 50))