log likelihood and derivatives for Unif distribution

Usage

llikUnif(x, alpha, beta, full = FALSE)

Arguments

x: variable distributed by a uniform distribution
alpha: is the lower limit of the uniform distribution
beta: is the upper limit of the distribution
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 llikUnif() but you have to use the x and rate arguments. You can also get the derivative of alpha or beta with llikUnifDalpha() and llikUnifDbeta().

Author

Matthew L. Fidler

Examples


# \donttest{

llikUnif(1, -2, 2)
#>          fx dAlpha dBeta
#> 1 -1.386294   0.25 -0.25

et  <- et(seq(1,1, length.out=4))
et$alpha <- -2
et$beta <- 2
 
model <- function() {
  model({
    fx <- llikUnif(time, alpha, beta)
    dAlpha<- llikUnifDalpha(time, alpha, beta)
    dBeta <- llikUnifDbeta(time, alpha, beta)
  })
}

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: 4 × 6
#>    time    fx dAlpha dBeta alpha  beta
#>   <dbl> <dbl>  <dbl> <dbl> <dbl> <dbl>
#> 1     1 -1.39   0.25 -0.25    -2     2
#> 2     1 -1.39   0.25 -0.25    -2     2
#> 3     1 -1.39   0.25 -0.25    -2     2
#> 4     1 -1.39   0.25 -0.25    -2     2
# }