Compute expected measurements from fitted models

Source: R/get_expected.R

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,
  dopar = TRUE
)

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.
dopar

Logical indicating whether to run calculations in parallel if a parallel backend is already set up, e.g., using doParallel::registerDoParallel(). Recommended to minimize runtime.

Value

A data.table.

See also

getModelFit(), getPosteriorFit(), getPosteriorSamples(), getExpectedMeasIntervals()