PCMMeanAtTime | R Documentation |
Calculate the mean at time t, given X0, under a PCM model
PCMMeanAtTime( t, model, X0 = model$X0, regime = PCMRegimes(model)[1L], verbose = FALSE )
t |
positive numeric denoting time |
model |
a PCM model object |
X0 |
a numeric vector of length k, where k is the number of traits in the model (Defaults to model$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). |
A numeric vector of length k
# 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)
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