getExpectedMeas | R Documentation |
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).
getExpectedMeas(
fit,
times,
fitType = c("posterior_mean", "posterior_samples", "raw"),
features = NULL,
dopar = TRUE
)
fit |
A 'limorhyde2' object. |
times |
Numeric vector of times, in units of
|
fitType |
String indicating which fitted models to use to compute the
expected measurements. A typical analysis using |
features |
Vector of names, row numbers, or logical values for
subsetting the features. |
dopar |
Logical indicating whether to run calculations in parallel if
a parallel backend is already set up, e.g., using
|
A data.table
.
getModelFit()
, getPosteriorFit()
, getPosteriorSamples()
,
getExpectedMeasIntervals()
library('data.table')
y = GSE34018$y
metadata = GSE34018$metadata
fit = getModelFit(y, metadata)
fit = getPosteriorFit(fit)
measObs = mergeMeasMeta(y, metadata, features = c('13170', '12686'))
measFitMean = getExpectedMeas(
fit, times = seq(0, 24, 0.5), features = c('13170', '12686'))
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