ornstein_uhlenbeck_sl {StratPal} | R Documentation |
Simulates an Ornstein-Uhlenbeck process on specimen level (_sl). The mean trait value is simulated using the Euler-Maruyama method. The process is simulated on a scale of 0.25 * min(diff(t))
and then interpolated to the values of t
. At each sampling location there are n_per_sample
specimens that are normally distributed around the mean trait value with a variance of intrapop_var
.
ornstein_uhlenbeck_sl(
t,
mu = 0,
theta = 1,
sigma = 1,
y0 = 0,
intrapop_var = 1,
n_per_sample = 10
)
t |
times at which the process is simulated. Can be heterodistant |
mu |
number, long term mean |
theta |
number, mean reversion speed |
sigma |
positive number, strength of randomness |
y0 |
number, initial value (value of process at the first entry of t) |
intrapop_var |
intrapopulation variance, determines how much specimens from the same population vary |
n_per_sample |
integer, number of specimens sampled per population/sampling locality |
an object of S3 class pre_paleoTS
, inherits from timelist
and list
. The list has two elements: t
, containing a vector of times of sampling, and vals
, a list of trait values of the same length as t
, with element containing trait values of individual specimens. This object can be transformed using apply_taphonomy
, apply_niche
or time_to_strat
, and then reduced to a paleoTS
object using reduce_to_paleoTS
. This can then be used to test for different modes of evolution.
ornstein_uhlenbeck()
to model mean trait values,
reduce_to_paleoTS()
to transform outputs into paleoTS
format
stasis_sl()
, strict_stasis_sl()
and random_walk_sl()
to simulate other modes of evolution
library("paleoTS")
x = ornstein_uhlenbeck_sl(1:5)
y = reduce_to_paleoTS(x) # turn into paleoTS format
plot(y) # plot using the paleoTS package
# see also
#vignette("paleoTS_functionality")
#for details and advanced usage