sens_lnorm: Adjust Log-Normal Distribution Parameters for Sensitivity...

In extras: Helper Functions for Bayesian Analyses

Adjust Log-Normal Distribution Parameters for Sensitivity Analysis

Description

Expands (sd_mult > 1) or reduces (sd_mult < 1) the standard deviation of the Log-Normal distribution. With high values of sdlog (i.e., ⁠> 9⁠), and sd_mult > 1, the mean of the adjusted distribution can be expected to have a mean value that is very different from the original mean, however, the proportional difference in these values should not be very different.

Usage

sens_lnorm(meanlog, sdlog, sd_mult = 2)

Arguments

meanlog	A numeric vector of the means on the log scale.
sdlog	A non-negative numeric vector of the standard deviations on the log scale.
sd_mult	A non-negative multiplier on the standard deviation of the distribution.

Value

A named list of the adjusted distribution's parameters.

See Also

Other sens_dist: sens_beta(), sens_exp(), sens_gamma(), sens_gamma_pois(), sens_gamma_pois_zi(), sens_neg_binom(), sens_norm(), sens_pois(), sens_skewnorm(), sens_student()

Examples

sens_lnorm(0, 1, 2)
sens_lnorm(0, 1, 0.8)

extras documentation built on April 4, 2025, 2:40 a.m.