log likelihood and derivatives for chi-squared distribution

Usage

llikChisq(x, df, full = FALSE)

Arguments

x: variable that is distributed by chi-squared distribution
df: degrees of freedom (non-negative, but can be non-integer).
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 dDf

that has the derivatives with respect to the df parameter the observation time-point

Details

In an rxode2() model, you can use llikChisq() but you have to use the x and df arguments. You can also get the derivative of df with llikChisqDdf().

Author

Matthew L. Fidler

Examples


# \donttest{
llikChisq(1, df = 1:3, full=TRUE)
#>   x df        fx         dDf
#> 1 1  1 -1.418939  0.63518142
#> 2 1  2 -1.193147 -0.05796576
#> 3 1  3 -1.418939 -0.36481858

llikChisq(1, df = 6:9)
#>          fx        dDf
#> 1 -3.272589 -0.8079658
#> 2 -4.126989 -0.8981519
#> 3 -5.064348 -0.9746324
#> 4 -6.072899 -1.0410091

et <- et(1:3)
et$x <- 1

model <- function() {
  model({
   fx <- llikChisq(x, time)
   dDf <- llikChisqDdf(x, time)
  })
}

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: 3 × 4
#>    time    fx     dDf     x
#>   <dbl> <dbl>   <dbl> <dbl>
#> 1     1 -1.42  0.635      1
#> 2     2 -1.19 -0.0580     1
#> 3     3 -1.42 -0.365      1
# }