chemdeg (version 0.1.2)

FOMT: First-Order Multi-Target model regression

Description

The function performs a non-linear regression using the first-order multi-target model. The model equation is: $$\frac{S}{S_0}=1-(1-e^{-k\,t})^m$$ where \(S/S_0\) is the fraction of surviving molecules, \(k\) is the average number of hits per time unit, \(m\) is the number of hits required to degrade the molecule, and \(t\) is time.

Usage

FOMT(dtframe)

Value

Returns the results of the regression as a nls object.

Arguments

dtframe

A data-frame containing 2 or 3 columns: time, normalized concentration and error (optional), respectively

Details

The FOMT model has been proposed as an alternative to the Weibull equation that is commonly used when the time-dependent behavior of the data significantly deviates from that predicted by standard chemical models.

See Also

FOMTm(), par_est_FOMT()

Examples

t <- c(0, 4, 8, 12, 16, 20)
conc <- c(1, 0.98, 0.99, 0.67, 0.12, 0.03)
err <- c(0.02, 0.05, 0.04, 0.04, 0.03, 0.02)
dframe <- data.frame(t, conc, err)
FOMT <- FOMT(dframe)
plot(dframe[[1]], dframe[[2]])
arrows(dframe[[1]], dframe[[2]] + dframe[[3]],
  dframe[[1]], dframe[[2]] - dframe[[3]],
  length = 0
)
newt <- seq(0, 21, by = 0.1)
lines(newt, predict(FOMT, newdata = list(t = newt)))

dframe1 <- data.frame(t, conc)
FOMT1 <- FOMT(dframe1)
plot(dframe1[[1]], dframe1[[2]])
lines(newt, predict(FOMT1, newdata = list(t = newt)))
summary(FOMT)
summary(FOMT1)