neg_log_lik_integrated: Negative marginalized log-likelihood function based on R0 and...

In pempi: Proportion Estimation with Marginal Proxy Information

Negative marginalized log-likelihood function based on R0 and R

Description

Log-Likelihood function based on R1 and R3 multiplied by -1.

Usage

neg_log_lik_integrated(theta, Rvect, n, pi0, alpha0, alpha, beta, ...)

Arguments

theta	A numeric value for the paramerer of interest.
Rvect	A vector of observations, i.e. (R1, R2, R3, R4), but R2 and R4 are NOT used.
n	A numeric that provides the sample size.
pi0	A numeric that provides the prevalence or proportion of people (in the whole population) who are positive, as measured through a non-random, but systematic sampling (e.g. based on medical selection).
alpha0	A numeric that corresponds to the probability that a random participant has been incorrectly declared positive through the nontransparent procedure. In most applications, this probability is likely very close to zero.
alpha	A numeric that provides the False Negative (FN) rate for the sample R.
beta	A numeric that provides the False Positive (FP) rate for the sample R.
...	Additional arguments.

Value

Negative marginalized log-likelihood.

Author(s)

Stephane Guerrier

pempi documentation built on Oct. 9, 2023, 5:10 p.m.