Generates a new model of class loadModel (loadModel-class).
Usage
loadModel(
inner.fit.function,
pred.format,
data,
metadata,
y.trans.function = NULL,
retrans.function = exp,
store = c("data", "fitting.function")
)Arguments
- inner.fit.function
function that accepts one argument, a training data frame, and returns a [re]fitted statistical model, such as an
lm, relating flux or concentration to predictors in the training data.- pred.format
character string that describes the output of retrans.function(predict(fit)) [NOT of predictSolute.loadModel(), which can do either!]
- data
data.frame containing the initial training observations
- metadata
An object of class
metadata- y.trans.function
function that accepts a vector of observed response values (e.g., concentrations or flux rates) and transforms them into the values on the left-hand side of the calibration formula. Because load models are frequently fit to log(y) ~ ..., the default is y.trans.function=log.
- retrans.function
function that accepts a vector of predictions straight from the fitted model and retransforms them, if appropriate, to predictions in linear space and with units of concentration*flow. Because load models are frequently fit to log(y) ~ ..., the default is retrans.function=exp. After retrans.function has been applied to the predictions, the retransformed predictions will automatically undergo further units conversion from conc*flow to load.rate, according to the metadata elements conc.units, flow.units, and load.rate.units.
- store
One or more character strings specifying which information to write within the model. Options are 'data': the original fitting data; 'fitting.function': a fitting function that can produce a new loadComp object from new data
See also
Other load.model.inits:
loadComp(),
loadInterp(),
loadLm(),
loadReg2()