logistft: Logistic model for the parametric nonlinear mixed effects...

In unkyunglee/HDChangePoint: Estimating disease onset from change points of markers measured with error

Description

Logistic model for the parametric nonlinear mixed effects model (nlme) procedure

Usage

logistft(theta1, theta2, theta3, logage)

Arguments

theta1	a scale parameter, which determines steepness of the logistic model.
theta2	a parameter for an inflection point.
theta3	a parameter, which determines the maximum (asymptote) of the logistic model.
logage	a vector of time points (log-scaled ages), which is generated around theta2. It can be an any length of numeric vector.

Value

a vector of response variables under the deterministic logistic model, whose length is the same as the length of logage.

Examples

library(HDChangePoint)

## Specify parameters
theta1=6;
theta2=0;
theta3=1;


## Specify the time points (log-scaled ages)
logage<-seq(-0.5, 0.5, by=0.1)

## Obtain a vector of response variables when parametric NLME assumes the logistic model
logit.ft<-logistft(6, 0, 1, logage)

## Plot the S-shaped curve under the logistic model
plot(logage, logit.ft, type='l')

unkyunglee/HDChangePoint documentation built on Nov. 27, 2021, 2:57 p.m.