Compute expected measurements from fitted models

This function computes expected measurements (corresponding to the fitted curves) for the specified times and features in all combinations of conditions and covariates (if they exist). Register a parallel backend to minimize runtime, e.g., using doParallel::registerDoParallel().

getExpectedMeas(
  fit,
  times,
  fitType = c("posterior_mean", "posterior_samples", "raw"),
  features = NULL
)

Arguments

fit	A 'limorhyde2' object.
times	Numeric vector of times, in units of `fit$metadata[[fit$timeColname]]`.
fitType	String indicating which fitted models to use to compute the expected measurements. A typical analysis using `limorhyde2` will be based on 'posterior_mean', the default.
features	Vector of names, row numbers, or logical values for subsetting the features. `NULL` indicates all features.

Value

A data.table.

Arguments

Value

See also