cppMLE {PoDBAY} | R Documentation |
Maximum likelihood estimation: cpp
Description
Function calculates the log likelihood value which is used after the initial guesses of the parameters are set in the PoDMLE
function.
Usage
cppMLE(params,
nondiseasedTiters,
diseasedTiters,
adjustTiters = FALSE,
adjustFrom = log2(10),
adjustTo = log2(5))
Arguments
params |
named numeric vector: PoD curve parameters ("et50", "slope", "pmax") |
nondiseasedTiters |
numeric vector: non-diseased subjects titers |
diseasedTiters |
numeric vector: diseased subjects titers |
adjustTiters |
boolean: set to TRUE if titer values should be adjusted, for details see |
adjustFrom |
numeric: value specifying the detection limit, all values below the detection limit will be adjusted to adjustTo value |
adjustTo |
numeric: value to which titers below the detection limit will be adjusted |
Details
cppMLE function is used inside of PoDMLE function and estimates the PoD curve paramers.
Based on the provided titers for diseased and non-diseased groups the PoD curve parameters which maximize the log likelihood are chosen as optimal.
Difference between MLE and cppMLE is only that cppMLE use cppPoD function instead of PoD. This step significantly improves the computation speed and provides the same results.
Value
log likelihood, numeric value
Examples
# Data preparation
data(diseased)
data(nondiseased)
data(PoDParams)
# MLE calculation
cppMLE(PoDParams, nondiseased$titers, diseased$titers)