Description Usage Arguments Details Value Author(s) See Also Examples
Estimates actual underlying concentrations leading to a given set of response measurements based on the assumption that actual concentrations are log-normally distributed around target concentrations, response errors are normally distributed, and the actual underlying relationship between concentration and response is represented by the given Hill dose-response model.
1 | hillConcCorrect(conc, act, parv, sigr = 1)
|
conc |
a vector of expected or target concentrations, around which actual concentrations are assumed to be log-normally distributed |
act |
a vector of response values |
parv |
a four-parameter vector specifying a Hill model as described in |
sigr |
the estimated ratio of the noises in response- and log (base10) concentration-space |
Suppose that c' is a given target concentration, and c is the actual concentration in given well, plate, or condition. Suppose also that y is the actual response that would result from the concentration in the given Hill dose-response model, and y' is the measured response value. This function assumes that
y' ~ N(y,sigma)
log10(c) ~ N(log10(c'),sigma/r)
for some sigma, where N is a normal distribution, and r is the ratio specified by the parameter sigr
.
Based on these assumptions, the function uses Bayes' rule to calculate the maximum likelihood estimate of c for every given
value of c' and y'.
A vector of concentrations representing the maximum likelihood estimates of the actual concentrations which produced the given responses.
Nathaniel R. Twarog
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