log likelihood and derivatives for Unif distribution

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)
#>  
#>  
#> 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 11.4.0-1ubuntu1~22.04) 11.4.0’
#> ── Solved rxode2 object ──
#> ── Parameters (value$params): ──
#> # A tibble: 1 × 0
#> ── Initial Conditions (value$inits): ──
#> named numeric(0)
#> ── First part of data (object): ──
#> # A tibble: 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
# }