cppMLE: Maximum likelihood estimation: cpp

Description Usage Arguments Details Value Examples

View source: R/FunctionsPoDParameters.R

Description

Function calculates the log likelihood value which is used after the initial guesses of the parameters are set in the PoDMLE function.

Usage

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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 PoD function

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

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# Data preparation
data(diseased)
data(nondiseased)
data(PoDParams)

# MLE calculation
cppMLE(PoDParams, nondiseased$titers, diseased$titers)

PoDBAY documentation built on Sept. 21, 2021, 5:08 p.m.