gasfluxes (version 0.4)

rlin.fit: Robust linear concentration - time model

Description

Fit a linear model to concentration - time data using robust methods.

Usage

rlin.fit(t, C, A = 1, V, serie = "", verbose = TRUE, plot = FALSE,
  ...)

Arguments

t

time values (usually in hours)

C

concentration values

A

area covered by the chamber

V

effective volume of the chamber

serie

id of the flux measurement

verbose

logical, TRUE prints message after each flux calculation

plot

logical, mainly intended for use in gasfluxes

…

further parameters, currently none

Value

A list of

f0

flux estimate

f0.se

standard error of flux estimate

f0.p

p-value of flux estimate

C0

estimated concentration at t = 0 (intercept)

weights

robustness weights

diagnostics

error or warning messages

Details

This is basically a wrapper of rlm using the Huber M estimator. This function never weights the first or last time point with zero with very few data points. However, there might exist "better" robust regression methods for flux estimation.

Examples

# NOT RUN {
#a single fit
t <- c(0, 1/3, 2/3, 1)
C <- c(320, 330, 315, 351)
print(fit <- rlin.fit(t, C, 1, 0.3, "a"))
plot(C ~ t)
curve({fit$f0/0.3 * x + fit$C0}, from = 0, to = 1, add = TRUE)

# }