tci (version 0.2.0)

log_likelihood: Evaluate the log likelihood of a vector of parameter values

Description

Evaluate the log liklihood of parameters given observed data. Can be applied to PK or PK-PD models.

Usage

log_likelihood(lpars, pkmod, inf, tms, obs)

Value

Numeric value of length 1

Arguments

lpars

Named vector of logged parameter values to be evaluated. This should include any PK or PD parameters, as well as residual error standard deviations (sigma_add or sigma_mult) that are to be evaluated.

pkmod

`pkmod` object. Mean values are a subset of log(pars_pk), log(pars_pd), log(sigma_add), log(sigma_mult). PK-PD parameter values not specified in `lpars` will be inferred from `pkmod`.

inf

Infusion schedule

tms

Times associated with observations

obs

Observed values (concentrations or PD response values)

Examples

my_mod <- pkmod(pars_pk = c(cl = 10, q2 = 2, q3 =20, v = 15, v2 = 30, v3 = 50,
 ke0 = 1.2), sigma_mult = 0.2)
inf <- inf_manual(inf_tms = 0, inf_rate = 80, duration = 2)
tms <- c(1,2,4,8,12)
obs <- simulate(my_mod, inf = inf, tms = tms)
# evaluate log-likelihood at a new set of parameters
lpars = log(c(cl=11,q2=3,q3=25,v=15,v2=30,v3=50,ke0=1.15,sigma_mult=0.3))
log_likelihood(lpars, my_mod, inf, tms, obs)

# estimate for a subset of parameters (exclude q2, v2, v3)
lpars_sub = log(c(cl=11,q3=25,v=15,ke0=1.15,sigma_mult=0.3))
log_likelihood(lpars_sub, my_mod, inf, tms, obs)

# add a pd response and replace multiplicative error with additive error
my_mod_pd <- update(my_mod, pars_pd = c(c50 = 2.8, gamma = 1.47, e0 = 93,
emx = 93), pdfn = emax, pdinv = emax_inv, ecmpt = 4, sigma_mult = 0, sigma_add = 4)
# simulate observations
obs_pd <- simulate(my_mod_pd, inf = inf, tms = seq(0,12,0.5))
# evaluate likelihood at new parameters
lpars_pd <- log(c(cl=11,q3=25,v=15,ke0=1.15,sigma_add=4,c50=5,gamma=1))
log_likelihood(lpars_pd, my_mod_pd, inf, tms = seq(0,12,0.5), obs_pd)