gen_wald_interval: Generate a Wald-type prediction interval for qPCR

In statdivlab/paramedic: Predicting Absolute and Relative Abundance by Modeling Efficiency to Derive Intervals and Concentrations

Generate a Wald-type prediction interval for qPCR

Description

Return a Wald-type prediction interval for qPCR values given the estimated concentrations.

Usage

gen_wald_interval(mu, sd, alpha = 0.05, truncate = TRUE)

Arguments

mu	the estimated concentrations (a vector of length N times q).
sd	the estimated standard deviation of the estimated concentrations (a vector of length N times q).
alpha	the desired level (defaults to 0.05, corresponding to a 95% interval).
truncate	truncate negative lower limits at zero (defaults to TRUE)

Value

A (1 - \alpha)x100% Wald-type prediction interval for each qPCR

Examples

# load the package, read in example data
library("paramedic")
data(example_16S_data)
data(example_qPCR_data)

# run paramedic (with an extremely small number of iterations, for illustration only)
# on only first 10 taxa
mod <- run_paramedic(W = example_16S_data[, 1:10], V = example_qPCR_data,
n_iter = 30, n_burnin = 25, 
n_chains = 1, stan_seed = 4747)
# get model summary
mod_summ <- rstan::summary(mod, probs = c(0.025, 0.975))$summary
# get samples
mod_samps <- rstan::extract(mod$stan_fit)
# extract relevant summaries
summs <- extract_posterior_summaries(stan_mod = mod_summ, stan_samps = mod_samps, 
taxa_of_interest = 1:3,
mult_num = 1, level = 0.95, interval_type = "wald")

statdivlab/paramedic documentation built on May 3, 2024, 7:08 p.m.