sigmoid: Sigmoid Function

In maomlab/BayesPharma: Tools for Bayesian Analysis of Non-Linear Pharmacology Models

Sigmoid Function

Description

Functional form for the sigmoid model.

Usage

sigmoid(ac50, hill, top, bottom, log_dose)

Arguments

ac50	numeric, the log_dose of half maximal activity
hill	numeric, slope of curve at the ac50 units of response/log_dose
top	numeric, value of maximal response for positive slope, this occurs when log_dose = Inf, with negative slope when log_dose = -Inf
bottom	numeric, value of minimal response for positive slope, this occurs when log_dose = -Inf, with negative slope when log_dose = Inf
log_dose	numeric, where to evaluate the the response where the log is base 10.

Value

numeric, response given the log_dose and parameters

See Also

sigmoid_model

Examples

## Not run: 
 # Generate an agonist curve with an ec50 of 1 μM with the response
 # normalized to [0, 1] over the range 100 nM to 10 μM with half-log steps
 data <- data.frame(
   log_dose = seq(-7, -5, length.out = 5)) |>
     dplyr::mutate(
       response = stats::rnorm(
         n = length(log_dose),
         mean = BayesPharma::sigmoid(
           ac50 = -6,
           hill = 1,
           top = 1,
           bottom = 0,
           log_dose = log_dose),
       sd = .2))

## End(Not run)

maomlab/BayesPharma documentation built on Aug. 24, 2024, 8:45 a.m.