getExpectedMeasIntervals {limorhyde2} | R Documentation |
Compute credible intervals for expected measurements
Description
This functions uses posterior samples to quantify uncertainty in the expected measurements from fitted models.
Usage
getExpectedMeasIntervals(expectedMeas, mass = 0.9, method = c("eti", "hdi"))
Arguments
expectedMeas |
A |
mass |
Number between 0 and 1 indicating the probability mass for which to calculate the intervals. |
method |
String indicating the type of interval: 'eti' for equal-tailed
using |
Value
A data.table
containing lower and upper bounds of the expected
measurement for each combination of feature, time, and possibly condition
and covariate.
See Also
getExpectedMeas()
, getStatsIntervals()
Examples
library('data.table')
y = GSE34018$y
metadata = GSE34018$metadata
fit = getModelFit(y, metadata)
fit = getPosteriorFit(fit)
fit = getPosteriorSamples(fit, nPosteriorSamples = 10L)
measFitSamps = getExpectedMeas(
fit, times = seq(0, 24, 0.5), fitType = 'posterior_samples',
features = c('13170', '12686'))
measFitInts = getExpectedMeasIntervals(measFitSamps)
[Package limorhyde2 version 0.1.0 Index]