.nll {serocalculator} | R Documentation |
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 per 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
[Package
serocalculator version 1.0.3
Index]