lc_loglik: Calculate the log likelihood of left censored lognormal data.

In ccb60/LCensMeans: Calculate Condtional Means of Left Censored Data

Description

Calculate the log likelihood of left censored lognormal data. The log likelihood has two parts – a term for observed values over the detection limit, and term for censored values (where all we know is that the value falls below the detection limit).

Usage

lc_loglik(params, cc, flg)

Arguments

params	A two item list or vector containing the mean and sd of the distribution on the log scale (i.e., the parameters of the related normal distribution).
cc	A vector of data values, including both observed values, where they exist, or the detection limits, where data was censored.
flg	A vector of TRUE or FALSE values, of the same length as cc, that indicates which values are detection limits (TRUE) and which are measured values (FALSE)

Value

The calculated log likelihood under a censored lognormal distribution with the specific parameters.

Examples

df <- data.frame(sim = sort(stats::rlnorm(25,2,3)),
                  cens=c(rep.int(TRUE,5), rep.int(FALSE,20)))
df$sim[1:4] <- df$sim[5]
lc_loglik(c(2,5), df$sim, df$cens)
lc_loglik(c(2,3), df$sim, df$cens)
lc_loglik(c(1,3), df$sim, df$cens)

ccb60/LCensMeans documentation built on Oct. 30, 2020, 3:26 a.m.