dot-nll: Calculate negative log-likelihood

In serocalculator: Estimating Infection Rates from Serological Data

Calculate negative log-likelihood

Description

Same as log_likelihood(), except negated and requiring lambda on log scale (used in combination with nlm(), to ensure that the optimization search doesn't stray into negative values of lambda).

Usage

.nll(log.lambda, ...)

Arguments

log.lambda

natural logarithm of incidence rate

...

Arguments passed on to log_likelihood pop_data a data.frame() with cross-sectional serology data by antibody and age, and additional columns antigen_isos Character vector listing one or more antigen isotypes. Values must match pop_data. curve_params a data.frame() containing MCMC samples of parameters from the Bayesian posterior distribution of a longitudinal decay curve model. The parameter columns must be named: antigen_iso: a character() vector indicating antigen-isotype combinations iter: an integer() vector indicating MCMC sampling iterations y0: baseline antibody level at $t=0$ ($y(t=0)$) y1: antibody peak level (ELISA units) t1: duration of infection alpha: antibody decay rate (1/days for the current longitudinal parameter sets) r: shape factor of antibody decay noise_params a data.frame() (or tibble::tibble()) containing the following variables, specifying noise parameters for each antigen isotype: antigen_iso: antigen isotype whose noise parameters are being specified on each row nu: biological noise eps: measurement noise y.low: lower limit of detection for the current antigen isotype y.high: upper limit of detection for the current antigen isotype verbose logical: if TRUE, print verbose log information to console

Value

the negative log-likelihood of the data with the current parameter values

serocalculator documentation built on April 3, 2025, 7:35 p.m.