FOMT {chemdeg}

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)

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.

Value

Returns the results of the regression as a nls object.

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)