Calculate negative log-likelihood (deviance) for one antigen:isotype pair and one incidence rate

Description

Calculate negative log-likelihood (deviance) for one antigen:isotype pair and one incidence rate

Usage

f_dev0(lambda, csdata, lnpars, cond)

Arguments

lambda	numeric() incidence parameter, in events per person-year
csdata	cross-sectional sample data containing variables value and age
lnpars	longitudinal antibody decay model parameters alpha, y1, and d
cond	measurement noise parameters nu, eps, y.low, and y.high

Details

interface with C lib serocalc.so

Value

a numeric() negative log-likelihood, corresponding to input lambda

Examples

library("serocalculator")

library(dplyr)
library(tibble)

# load in longitudinal parameters
curve_params <-
  typhoid_curves_nostrat_100 |>
  filter(antigen_iso %in% c("HlyE_IgA", "HlyE_IgG"))

# load in pop data
xs_data <-
  sees_pop_data_pk_100

# Load noise params
noise_params <- tibble(
  antigen_iso = c("HlyE_IgG", "HlyE_IgA"),
  nu = c(0.5, 0.5), # Biologic noise (nu)
  eps = c(0, 0), # M noise (eps)
  y.low = c(1, 1), # low cutoff (llod)
  y.high = c(5e6, 5e6)
) # high cutoff (y.high)

cur_antibody <- "HlyE_IgA"

cur_data <-
  xs_data |>
  dplyr::filter(
    .data$antigen_iso == cur_antibody
  ) |>
  dplyr::slice_head(n = 100)

cur_curve_params <-
  curve_params |>
  dplyr::filter(.data$antigen_iso == cur_antibody) |>
  dplyr::slice_head(n = 100)

cur_noise_params <-
  noise_params |>
  dplyr::filter(.data$antigen_iso == cur_antibody)

if (!is.element("d", names(cur_curve_params))) {
  cur_curve_params <-
    cur_curve_params |>
    dplyr::mutate(
      alpha = .data$alpha * 365.25,
      d = .data$r - 1
    )
}

lambda <- 0.1
f_dev0(
  lambda = lambda,
  csdata = cur_data,
  lnpars = cur_curve_params,
  cond = cur_noise_params
)