llikBeta: Calculate the log likelihood of the binomial function (and...

In rxode2: Facilities for Simulating from ODE-Based Models

Calculate the log likelihood of the binomial function (and its derivatives)

Description

Calculate the log likelihood of the binomial function (and its derivatives)

Usage

llikBeta(x, shape1, shape2, full = FALSE)

Arguments

x	Observation
shape1, shape2	non-negative parameters of the Beta distribution.
full	Add the data frame showing x, mean, sd as well as the fx and derivatives

Details

In an rxode2() model, you can use llikBeta() but you have to use all arguments. You can also get the derivative of shape1 and shape2 with llikBetaDshape1() and llikBetaDshape2().

Value

data frame with fx for the log pdf value of with dShape1 and dShape2 that has the derivatives with respect to the parameters at the observation time-point

Author(s)

Matthew L. Fidler

Examples

x <- seq(1e-4, 1 - 1e-4, length.out = 21)

llikBeta(x, 0.5, 0.5)

llikBeta(x, 1, 3, TRUE)

et <- et(seq(1e-4, 1-1e-4, length.out=21))
et$shape1 <- 0.5
et$shape2 <- 1.5

model <- function() {
  model({
    fx <- llikBeta(time, shape1, shape2)
    dShape1 <- llikBetaDshape1(time, shape1, shape2)
    dShape2 <- llikBetaDshape2(time, shape1, shape2)
  })
}

rxSolve(model, et)

rxode2 documentation built on Oct. 30, 2024, 9:06 a.m.