
Calculate the log likelihood of the negative binomial function (and its derivatives)
Source:R/llik.R
      llikNbinom.RdCalculate the log likelihood of the negative binomial function (and its derivatives)
Value
data frame with fx for the pdf value of with
dProb that has the derivatives with respect to the parameters at
the observation time-point
Details
In an rxode2() model, you can use llikNbinom() but you have to
use all arguments.  You can also get the derivative of prob with
llikNbinomDprob()
Examples
# \donttest{
llikNbinom(46:54, 100, 0.5)
#>          fx dProb
#> 1 -13.25200   108
#> 2 -12.81168   106
#> 3 -12.38560   104
#> 4 -11.97335   102
#> 5 -11.57458   100
#> 6 -11.18892    98
#> 7 -10.81603    96
#> 8 -10.45559    94
#> 9 -10.10728    92
llikNbinom(46:54, 100, 0.5, TRUE)
#>    x size prob        fx dProb
#> 1 46  100  0.5 -13.25200   108
#> 2 47  100  0.5 -12.81168   106
#> 3 48  100  0.5 -12.38560   104
#> 4 49  100  0.5 -11.97335   102
#> 5 50  100  0.5 -11.57458   100
#> 6 51  100  0.5 -11.18892    98
#> 7 52  100  0.5 -10.81603    96
#> 8 53  100  0.5 -10.45559    94
#> 9 54  100  0.5 -10.10728    92
# In rxode2 you can use:
et <- et(46:54)
et$size <- 100
et$prob <-0.5
model <- function() {
  model({
    fx <- llikNbinom(time, size, prob)
    dProb <- llikNbinomDprob(time, size, prob)
  })
}
rxSolve(model, et)
#>  
#>  
#> ℹ parameter labels from comments are typically ignored in non-interactive mode
#> ℹ Need to run with the source intact to parse comments
#>  
#>  
#> using C compiler: ‘gcc (Ubuntu 13.3.0-6ubuntu2~24.04) 13.3.0’
#> ── Solved rxode2 object ──
#> ── Parameters (value$params): ──
#> # A tibble: 1 × 0
#> ── Initial Conditions (value$inits): ──
#> named numeric(0)
#> ── First part of data (object): ──
#> # A tibble: 9 × 5
#>    time    fx dProb  size  prob
#>   <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1    46 -13.3   108   100   0.5
#> 2    47 -12.8   106   100   0.5
#> 3    48 -12.4   104   100   0.5
#> 4    49 -12.0   102   100   0.5
#> 5    50 -11.6   100   100   0.5
#> 6    51 -11.2    98   100   0.5
#> # ℹ 3 more rows
# }