simulate phenotypic stasis (specimen level)

simulates stasis as independent, normally distributed random variables with mean mean and standard deviation sd, draws n_per_sample samples from each sampling location (population) that have specified variance intrapop_var

Usage

stasis_sl(t, mean = 0, sd = 1, intrapop_var = 1, n_per_sample = 10)

Arguments

t

times at which the traits are determined

mean

mean trait value

sd

strictly positive number, standard deviation of traits around the mean

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

Value

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.

See also

• stasis() for the version that simulates stasis of mean trait values

• strict_stasis_sl() for more narrow definition of stasis

• reduce_to_paleoTS() to transform into the outputs into paleoTS format (e.g., for plotting or further analysis)

• random_walk_sl() and ornstein_uhlenbeck_sl() for other modes of evolution

Examples

library("paleoTS")
x = stasis_sl(1:5, mean = 2, sd = 2)
y = reduce_to_paleoTS(x) # turn into paleoTS format
plot(y) # plot using paleoTS package

# see also
#vignette("paleoTS_functionality")
#for details and advanced usage