llikGamma: log likelihood and derivatives for Gamma distribution

In nlmixr2/rxode2: Facilities for Simulating from ODE-Based Models

log likelihood and derivatives for Gamma distribution

Description

log likelihood and derivatives for Gamma distribution

Usage

llikGamma(x, shape, rate, full = FALSE)

Arguments

x	variable that is distributed by gamma distribution
shape	this is the distribution's shape parameter. Must be positive.
rate	this is the distribution's rate parameters. Must be positive.
full	Add the data frame showing x, mean, sd as well as the fx and derivatives

Details

In an rxode2() model, you can use llikGamma() but you have to use the x and rate arguments. You can also get the derivative of shape or rate with llikGammaDshape() and llikGammaDrate().

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

Author(s)

Matthew L. Fidler

Examples

llikGamma(1, 1, 10)

# You can use this in `rxode2` too:

et  <- et(seq(0.001, 1, length.out=10))
et$shape <- 1
et$rate <- 10
 
model <- function() {
  model({
    fx <- llikGamma(time, shape, rate)
    dShape<- llikGammaDshape(time, shape, rate)
    dRate <- llikGammaDrate(time, shape, rate)
  })
}

rxSolve(model, et)

nlmixr2/rxode2 documentation built on Jan. 11, 2025, 8:48 a.m.