simhetdecay2: Simulate two phase exponential decay data

In TJMurphy/nlfitr: Fitting models to nonlinear data

Description

A sandbox to simulate and visualize random normal heteroscedastic response data. Variances enlarge with the value of y predicted by the model using a constant coefficeint of variation (cv). The data generating formula is derived from the general model: "y = y0*e^-(k1+k2)x". A two-phase model is used when the outcome you measure is the result of the sum of a fast and slow exponential decay. This is also called a double exponential decay.Failure errors in the plot fitting subfunction will occasionally happen due to the random data. These are more frequent with higher cv values. Just re-simulate with modified parameter values. The regression formula is: 'y ~ range1*exp(-k1*x) + range2*exp(-k2*x) + ylo'

Usage

simhetdecay2(x, k1, k2, range1, range2, ylo, cv, reps)

Arguments

x	a vector of non-exponential linear scale values representing time.
k1	the first rate constant, expressed in reciprocal of the X axis time units. The first half-life is 0.6932/k1.
k2	the second rate constant, expressed in reciprocal of the X axis time units. The second half-life is 0.6932/k2.
range1	a single value for the range of y in the first phase of decay, in y units.
range2	a single value for the range of y in the second phase of decay, in y units..
ylo	the lowest expected y value, or the value at infinite times, expressed in the same units as Y.
cv	the coefficient of variation for y replicates.
reps	an integer value for number of replicates

Value

ggplot, data

Examples

# Note: exponential or log-transformed x scale values will not work
# do not use x = c(1e-9, 3e-9, ...) or c(-9, -8.523, ...)

time <- c(1, 5, 10, 15, 20, 25) # eg, in mins

set.seed(2345)

decay2dat <- simhetdecay2(time, k1 = 0.5, k2 = 0.2, range1 = 2, range2 = 10,
ylo = 1.0, cv = 0.10, reps = 5)

decay2dat

decay2dat$data

TJMurphy/nlfitr documentation built on March 18, 2021, 12:33 p.m.