pub fn co2_plants() -> Result<DataFrame, PolarsError>Expand description
§Carbon Dioxide Uptake in Grass Plants
§Description:
The ‘CO2’ data frame has 84 rows and 5 columns of data from an experiment on the cold tolerance of the grass species Echinochloa crus-galli.
§Usage:
CO2
§Format:
An object of class ‘c(“nfnGroupedData”, “nfGroupedData”, “groupedData”, “data.frame”)’ containing the following columns:
- Plant an ordered factor with levels ‘Qn1’ < ‘Qn2’ < ‘Qn3’ < … < ‘Mc1’ giving a unique identifier for each plant.
- Type a factor with levels ‘Quebec’ ‘Mississippi’ giving the origin of the plant
- Treatment a factor with levels ‘nonchilled’ ‘chilled’
- conc a numeric vector of ambient carbon dioxide concentrations (mL/L).
- uptake a numeric vector of carbon dioxide uptake rates (umol/m^2 sec).
§Details:
The CO2 uptake of six plants from Quebec and six plants from Mississippi was measured at several levels of ambient CO2 concentration. Half the plants of each type were chilled overnight before the experiment was conducted.
This dataset was originally part of package ‘nlme’, and that has methods (including for ‘[’, ‘as.data.frame’, ‘plot’ and ‘print’) for its grouped-data classes.
§Source:
Potvin, C., Lechowicz, M. J. and Tardif, S. (1990) “The statistical analysis of ecophysiological response curves obtained from experiments involving repeated measures”, Ecology, 71, 1389-1400.
Pinheiro, J. C. and Bates, D. M. (2000) Mixed-effects Models in S and S-PLUS, Springer.
§Examples:
require(stats); require(graphics)
coplot(uptake ~ conc | Plant, data = CO2, show.given = FALSE, type = "b")
## fit the data for the first plant
fm1 <- nls(uptake ~ SSasymp(conc, Asym, lrc, c0),
data = CO2, subset = Plant == "Qn1")
summary(fm1)
## fit each plant separately
fmlist <- list()
for (pp in levels(CO2$Plant)) {
fmlist[[pp]] <- nls(uptake ~ SSasymp(conc, Asym, lrc, c0),
data = CO2, subset = Plant == pp)
}
## check the coefficients by plant
print(sapply(fmlist, coef), digits = 3)