PCMParamBindRegimeParams {PCMBase}

Bind named vectors or matrices into an array so that the names form the names of the last dimension.

Description

Bind named vectors or matrices into an array so that the names form the names of the last dimension.

Usage

PCMParamBindRegimeParams(...)

Arguments

...

Any number of named vectors, or matrices. The dimensions of all the arrays must match. The names will be used for the names of the regimes.

Value

an array with dim attribute one longer than the number of dimensions of each argument, i.e. if there are 5 vector arguments of length 2, the returned value will be an array with dim c(2,5); if there are 5 matrix arguments of dim 2 x 2, the returned value will be an array with dim c(2,2,5).

Examples

# regimes

# in regime 'a' the three traits evolve according to three independent OU processes
a.X0 <- c(5, 2, 1)
a.H <- rbind(
  c(0, 0, 0),
  c(0, 2, 0),
  c(0, 0, 3))
a.Theta <- c(10, 6, 2)
a.Sigma_x <- rbind(
  c(1.6, 0.0, 0.0),
  c(0.0, 2.4, 0.0),
  c(0.0, 0.0, 2.0))
a.Sigmae_x <- rbind(
  c(0.0, 0.0, 0.0),
  c(0.0, 0.0, 0.0),
  c(0.0, 0.0, 0.0))
a.h_drift<-c(0, 0, 0)

# in regime 'b' there is correlation between the traits
b.X0 <- c(12, 4, 3)
b.H <- rbind(
  c(2.0, 0.1, 0.2),
  c(0.1, 0.6, 0.2),
  c(0.2, 0.2, 0.3))
b.Theta <- c(10, 6, 2)
b.Sigma_x <- rbind(
  c(1.6, 0.3, 0.3),
  c(0.0, 0.3, 0.4),
  c(0.0, 0.0, 2.0))
b.Sigmae_x <- rbind(
  c(0.2, 0.0, 0.0),
  c(0.0, 0.3, 0.0),
  c(0.0, 0.0, 0.4))
b.h_drift<-c(1, 2, 3)

H <- PCMParamBindRegimeParams(a = a.H, b = b.H)
Theta <- PCMParamBindRegimeParams(a = a.Theta, b = b.Theta)
Sigma_x <- PCMParamBindRegimeParams(a = a.Sigma_x, b = b.Sigma_x)
Sigmae_x <- PCMParamBindRegimeParams(a = a.Sigmae_x, b = b.Sigmae_x)
h_drift <- PCMParamBindRegimeParams(a = a.h_drift, b = b.h_drift)

model.a.BM_drift.123 <- PCM("BM_drift", k = 3, regimes = "a",
params = list(
  X0 = a.X0,
  h_drift = h_drift[,'a',drop=FALSE],
  Sigma_x = Sigma_x[,,'a',drop=FALSE],
  Sigmae_x = Sigmae_x[,,'a',drop=FALSE]))

# regimes 'a' and 'b', traits 1, 2 and 3
model.ab.123 <- PCM("OU", k = 3, regimes = c("a", "b"),
                    params = list(
                      X0 = a.X0,
                      H = H[,,,drop=FALSE],
                      Theta = Theta[,,drop=FALSE],
                      Sigma_x = Sigma_x[,,,drop=FALSE],
                      Sigmae_x = Sigmae_x[,,,drop=FALSE]))