modelfit-class: "Modelfit"
Slots
- model
- The chosen model, either
"Gaussian" or "EMG". - fitting
- The mode of fitting which generated the object. Either
"most_intense" or "model". - alphafunction
- A function of m/z that computes an estimate for the
EMG parameter alpha. See fitModelParameters for
more detailed information on this parameter. - sigmafunction
- A function of m/z that computes an estimate for the
EMG parameter sigma. See fitModelParameters for
more detailed information on this parameter. - mufunction
- A function of m/z that computes an estimate for the
EMG parameter mu. See fitModelParameters for
more detailed information on this parameter. - peakfitresults
- A
matrix of five columns if model =
"Gaussian" and of six columns if model = "EMG",
respectively. The matrix contains basic information on the extracted
peaks and the corresponding parameters. The first column contains the
number of (mz, intensity)-pairs used for fitting, the second column
contains the residual sums of squares of the model fit, the middle
columns the parameter estimates and the last column the m/z position. - bestpeak
- A
list containing detailed information on the
'best' peak, where 'best' is equivalent to 'minimum residual sums of
squares' after fitting. Mainly used indirectly by calling the function visualize.
Methods
- show
- Use
show(object) for brief information about the object. - visualize
- A function to display graphically the result of
parameter estimation. One can either visualize a single peak
(
slot(object, "bestpeak")) or the fit of the linear models
postulated for the parameters alpha, sigma and
mu. The function visualize is called with the following
set of parameters.
object- An object of class
modelfit. type- A
character specifying the object to be
visualized. If type = "peak",
the fit of a single peak stored in object@bestpeak is
displayed. If type = "model", one obtains scatterplots of the
form parameter vs. mz for each parameter in
parameters, s. below. parameters- Needed if and only if
type = "model" in
order to choose the y-variable of the scatterplot. Several parameters
may be specified at a time, in which case one obtains a multi-panel
plot. modelfit- A
logical indicating whether the estimated
regression functions should be added to the
scatterplots (if type = "model").