vaeCovariates: Covariates explored by the VAE covariate search

In nlmixr2est: Nonlinear Mixed Effects Models in Population PK/PD, Estimation Routines

Covariates explored by the VAE covariate search

Description

Returns the candidate columns that 'nlmixr2(..., est = "vae")' would explore during automated covariate selection, using the same discovery rules as the fit: every non-reserved data column that is constant within each subject is a candidate. A numeric candidate with more than two unique values is continuous and contributes one column per eligible shape; anything else is categorical and contributes an indicator per testable level. Columns sharing a 'group' are alternate shapes of one covariate, so at most one of them can enter a given parameter. Time-varying columns cannot be searched and are excluded with a warning.

Usage

vaeCovariates(
  data,
  warn = TRUE,
  shapes = c("power", "lin", "log", "identity", "center", "hockey"),
  covCenterType = c("median", "mean"),
  covCenter = NULL,
  catCutoff = 0.05
)

Arguments

data	estimation dataset containing at least an 'ID' column; column names are matched case-insensitively, as in the VAE fit
warn	when 'TRUE' (default) warn about time-varying columns excluded from the search; when 'FALSE' exclude them silently
shapes, covCenterType, covCenter, catCutoff	as in [vaeControl()]; control which shapes are explored and how covariates are centered

Value

a data frame with one row per candidate search column and columns 'covariate' (the column name), 'raw' (upper-cased data column it comes from), 'shape', 'level' (for categorical indicators), 'group' (mutual exclusion group), 'block' (columns selected all-or-none, i.e. the two arms of a '"hockey"' relationship), 'type' and 'center'; zero rows when nothing qualifies

Author(s)

Matthew L. Fidler

Examples

d <- data.frame(id = rep(1:3, each = 2), time = rep(0:1, 3), dv = rnorm(6),
                wt = rep(c(70, 80, 60), each = 2),
                sex = rep(c(0, 1, 0), each = 2))
vaeCovariates(d)

# restrict the explored shapes
vaeCovariates(d, shapes = "power")

nlmixr2est documentation built on Aug. 5, 2026, 1:11 a.m.