log likelihood and derivatives for Geom distribution
Arguments
- x
variable distributed by a geom distribution
- prob
probability of success in each trial.
0 < prob <= 1.- full
Add the data frame showing x, mean, sd as well as the fx and derivatives
Value
data frame with fx for the log pdf value of with dProb
that has the derivatives with respect to the prob parameters at
the observation time-point
Details
In an rxode2() model, you can use llikGeom() but you have to
use the x and rate arguments. You can also get the derivative of prob with
llikGeomDprob().
Examples
# \donttest{
llikGeom(1:10, 0.2)
#> fx dProb
#> 1 -1.832581 3.75
#> 2 -2.055725 2.50
#> 3 -2.278869 1.25
#> 4 -2.502012 0.00
#> 5 -2.725156 -1.25
#> 6 -2.948299 -2.50
#> 7 -3.171443 -3.75
#> 8 -3.394586 -5.00
#> 9 -3.617730 -6.25
#> 10 -3.840873 -7.50
et <- et(1:10)
et$prob <- 0.2
model <- function() {
model({
fx <- llikGeom(time, prob)
dProb <- llikGeomDprob(time, prob)
})
}
rxSolve(model, et)
#>
#>
#>
#>
#> using C compiler: ‘gcc (Ubuntu 11.4.0-1ubuntu1~22.04) 11.4.0’
#> ── Solved rxode2 object ──
#> ── Parameters ($params): ──
#> # A tibble: 1 × 0
#> ── Initial Conditions ($inits): ──
#> named numeric(0)
#> ── First part of data (object): ──
#> # A tibble: 10 × 4
#> time fx dProb prob
#> <dbl> <dbl> <dbl> <dbl>
#> 1 1 -1.83 3.75 0.2
#> 2 2 -2.06 2.5 0.2
#> 3 3 -2.28 1.25 0.2
#> 4 4 -2.50 0 0.2
#> 5 5 -2.73 -1.25 0.2
#> 6 6 -2.95 -2.5 0.2
#> # ℹ 4 more rows
# }