Description Usage Arguments Value Examples
A sandbox to simulate heteroscedastic exponential growth data. Random normal variance enlarges with the model value of y using a constant coefficeint of variation (cv). The data generating model is an exponential growth function: 'yp = ylo*exp(k*x)'. The random value is then produced by applying the following to a dataframe of yp values: 'y = rnorm(1, yp, cv*yp)'. The plot fitting subfunction will occasionally fail due to random data. These may occur with higher cv values, fewer reps, and fewer x values. Just re-simulate with modified parameter values. The regression formula is 'y ~ ylo*exp(k*x)'.
1 | simhetegro(x, k, ylo, cv, reps, weight = F)
|
x |
A vector of linear scale values. |
k |
A starting estimate for the rate constant, which has units of reciprocal x. |
ylo |
The lowest value of y, or starting value. |
cv |
The coefficient of variation. |
reps |
The number of replicates per value of x. |
weight |
A logical value indicating y scale weighting. Default is FALSE. If TRUE, the curve is fit using relative (1/y^2) weighting. |
ggplot, data
1 2 3 4 5 6 7 8 | # Hypothetical Cell growth measured every 4 hours, replicated 5 times
simu <- simhetegro(x=c(0, 4, 8, 12, 16, 20, 24, 28), k=0.2, ylo=100,
cv=0.3, reps=5, weight=FALSE)
simu
simu$data#'
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