elicit_exponential: Elicit an Exponential prior via moments, rate, or quantile...

In bayprior: Bayesian Prior Elicitation and Diagnostics for Clinical Trials

Elicit an Exponential prior via moments, rate, or quantile matching

Description

Fits an Exponential(rate) prior from expert-specified moments or quantiles. Suitable for constant-hazard survival models and Poisson rate priors. The Exponential distribution is the conjugate prior likelihood for a Gamma prior on the rate parameter.

Usage

elicit_exponential(
  rate = NULL,
  mean = NULL,
  quantiles = NULL,
  method = c("moments", "rate", "quantile"),
  expert_id = "Expert",
  label = "Quantity"
)

Arguments

rate	Numeric > 0. Rate parameter (= 1 / mean). Used when method = "rate".
mean	Numeric > 0. Prior mean (= 1 / rate). Used when method = "moments".
quantiles	Named numeric vector with at least one interior quantile. Used when method = "quantile".
method	Character. One of "moments", "rate", or "quantile". Default "moments".
expert_id	Character. Identifier for the eliciting expert.
label	Character. Human-readable label for the quantity.

Details

The Exponential distribution has a single parameter \lambda > 0 (the rate). Its mean is 1/\lambda and its SD equals its mean.

Typical use cases:

Hazard rates

OS/PFS hazard in oncology trials

Event rates

Adverse event rates (events per person-time)

Poisson rate priors

Conjugate prior for Poisson count data

Value

A bayprior object with dist = "exponential".

Examples

# Mean survival 20 months => hazard rate 1/20 = 0.05
p <- elicit_exponential(mean = 0.05, method = "moments",
                         label     = "Hazard rate",
                         expert_id = "Expert_1")
print(p)
plot(p)

# Direct rate specification
p2 <- elicit_exponential(rate = 0.10, method = "rate",
                          label = "AE rate per person-year")

# Quantile matching
p3 <- elicit_exponential(
  quantiles = c("0.25" = 0.02, "0.50" = 0.05, "0.75" = 0.10),
  method    = "quantile",
  label     = "Hazard rate"
)

bayprior documentation built on Aug. 27, 2026, 1:09 a.m.