Build a Temporal Covariance Sub-model

Wrapper around buildPedigreeModelCovariance with temporal = TRUE.

Usage

buildTemporalPedigreeModelCovariance(
  p_hist,
  components = c("a", "d", "cn", "ce", "mt", "e"),
  start_beta0 = 0.5,
  start_beta_time = 0,
  start_gamma = 0,
  time_point_max = NULL,
  mean_degree = 0,
  start_mean = 0,
  mean_hist_free = FALSE,
  start_mean_hist = 0
)

Arguments

p_hist

Integer. Number of historical moderator columns.

components

Character vector of component keys to include when temporal = TRUE (any of "a", "d", "cn", "ce", "mt", "am", "e"). Default is c("a", "e").

start_beta0

Numeric. Starting value for each component's intercept loading. Only used when temporal = TRUE. Default is 0.5.

start_beta_time

Numeric. Starting value for each component's time-slope loadings. Only used when temporal = TRUE. Default is 0.

start_gamma

Numeric. Starting value for historical-moderator loadings. Only used when temporal = TRUE. Default is 0.

time_point_max

Integer. Degree of the polynomial birth-year basis. Only used when temporal = TRUE. Default is 3.

mean_degree

Integer. Degree of the polynomial temporal mean. The default, 0, estimates a constant mean. Must not exceed time_point_max.

start_mean

Numeric. Starting value for the mean's intercept. Set this near the observed phenotype mean.

mean_hist_free

Logical, length 1 or p_hist. Whether historical moderators can shift the phenotypic mean. Defaults to FALSE, fixing those shifts at zero.

start_mean_hist

Numeric. Starting value for the free elements of G_mean.

Value

An OpenMx model containing the B_*/G_* parameter matrices.