log likelihood and derivatives for Weibull distribution

log likelihood and derivatives for Weibull distribution

Usage

llikWeibull(x, shape, scale, full = FALSE)

Arguments

x

variable distributed by a Weibull distribution

shape, scale

shape and scale parameters, the latter defaulting to 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 llikWeibull() but you have to use the x and rate arguments. You can also get the derivative of shape or scale with llikWeibullDshape() and llikWeibullDscale().

Author

Matthew L. Fidler

Examples

# \donttest{
llikWeibull(1, 1, 10)
#>          fx    dShape dScale
#> 1 -2.402585 -1.072327  -0.09

# rxode2 can use this too:

et  <- et(seq(0.001, 1, length.out=10))
et$shape <- 1
et$scale <- 10
 
model <- function() {
  model({
    fx <- llikWeibull(time, shape, scale)
    dShape<- llikWeibullDshape(time, shape, scale)
    dScale <- llikWeibullDscale(time, shape, scale)
  })
}

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 × 6
#>    time    fx dShape  dScale shape scale
#>   <dbl> <dbl>  <dbl>   <dbl> <dbl> <dbl>
#> 1 0.001 -2.30  -8.21 -0.100      1    10
#> 2 0.112 -2.31  -3.44 -0.0989     1    10
#> 3 0.223 -2.32  -2.72 -0.0978     1    10
#> 4 0.334 -2.34  -2.29 -0.0967     1    10
#> 5 0.445 -2.35  -1.97 -0.0956     1    10
#> 6 0.556 -2.36  -1.73 -0.0944     1    10
#> # ℹ 4 more rows
# }