PCMMeanAtTime {PCMBase}

Calculate the mean at time t, given X0, under a PCM model

Description

Calculate the mean at time t, given X0, under a PCM model

Usage

PCMMeanAtTime(
  t,
  model,
  X0 = model$X0,
  regime = PCMRegimes(model)[1L],
  verbose = FALSE
)

Arguments

t

positive numeric denoting time

model

a PCM model object

X0

a numeric vector of length k, where k is the number of traits in the model (Defaults to model$X0).

regime

an integer or a character denoting the regime in model for which to do the calculation; Defaults to PCMRegimes(model)[1L], meaning the first regime in the model.

verbose

a logical indicating if (debug) messages should be written on the console (Defaults to FALSE).

Value

A numeric vector of length k

Examples

# a Brownian motion model with one regime
modelBM <- PCM(model = "BM", k = 2)
# print the model
modelBM
# assign the model parameters at random: this will use uniform distribution
# with boundaries specified by PCMParamLowerLimit and PCMParamUpperLimit
# We do this in two steps:
# 1. First we generate a random vector. Note the length of the vector equals PCMParamCount(modelBM)
randomParams <- PCMParamRandomVecParams(modelBM, PCMNumTraits(modelBM), PCMNumRegimes(modelBM))
randomParams
# 2. Then we load this random vector into the model.
PCMParamLoadOrStore(modelBM, randomParams, 0, PCMNumTraits(modelBM), PCMNumRegimes(modelBM), TRUE)

# PCMMeanAtTime(1, modelBM)

# note that the variance at time 0 is not the 0 matrix because the model has a non-zero
# environmental deviation
PCMMeanAtTime(0, modelBM)