getExpectedMeasIntervals: Compute credible intervals for expected measurements

In limorhyde2: Quantify Rhythmicity and Differential Rhythmicity in Genomic Data

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 data.table of expected measurements for posterior samples, as returned by getExpectedMeas().
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 stats::quantile(), or 'hdi' for highest density using HDInterval::hdi().

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)

limorhyde2 documentation built on Feb. 16, 2023, 7:43 p.m.