feemjackknife: Jack-knife outlier detection in PARAFAC models

In albatross: PARAFAC Analysis of Fluorescence Excitation-Emission Matrices

Jack-knife outlier detection in PARAFAC models

Description

Perform leave-one-out fitting + validation of PARAFAC models on a given FEEM cube.

Usage

  feemjackknife(cube, ..., progress = TRUE)
  ## S3 method for class 'feemjackknife'
plot(
    x, kind = c('estimations', 'RIP', 'IMP'), ...
  )
  ## S3 method for class 'feemjackknife'
coef(
    object, kind = c('estimations', 'RIP', 'IMP'), ...
  )

Arguments

cube	A feemcube object.
progress	Set to FALSE to disable the progress bar.
x, object	An object returned by feemjackknife.
kind	Chooses what to plot (when called as plot(...)) or return as a data.frame (when called as coef(...)): estimations Produce the loadings from every leave-one-out model. RIP Produce a Resample Influence Plot, i.e. mean squared difference between loadings in overall and leave-one-out models plotted against mean squared residuals in leave-one-out models. IMP Produce an Identity Match Plot, i.e. scores in leave-one-out models plotted against scores in the overall model.
...	feemjackknife Passed as-is to feemparafac and, eventually, to multiway function parafac. plot.feemjackknife When kind is “RIP” or “IMP”, pass a q argument to specify the quantile of residual values (for RIP) or absolute score differences (IMP) above which sample names (or numbers) should be plotted. Default value for q is 0.9. Remaining arguments are passed as-is to xyplot. coef.feemjackknife No further parameters are allowed.

Details

The function takes each sample out of the dataset, fits a PARAFAC model without it, then fits the outstanding sample to the model with emission and excitation factors fixed:

3{ \hat{\mathbf{c}} = (\mathbf{A} \ast \mathbf{B})^{+} \times \mathrm{vec}(\mathbf{X})

Value

feemjackknife

A list of class feemjackknife containing the following entries:

overall

Result of fitting the overall cube with feemparafac.

leaveone

A list of length dim(cube)[3] containing the reduced dataset components. Every feemparafac object in the list has an additional Chat attribute containing the result of fitting the excluded spectrum back to the loadings of the reduced model.

plot.feemjackknife

A lattice plot object. Its print or plot method will draw the plot on an appropriate plotting device.

coef.feemjackknife

A data.frame containing various columns, depending on the value of the kind argument:

estimations

loading

Values of the loadings.

mode

The axis of the loadings, “Emission” or “Excitation”.

wavelength

Emission or excitation wavelength the loading values correspond to.

factor

The component number.

omitted

The sample (name if cube had names, integer if it didn't) that was omitted to get the resulting loading values.

RIP

msq.resid

Mean squared residual value for the model with a given sample omitted.

Emission

Mean squared difference in emission mode loadings between the overall model and the model with a given sample omitted.

Excitation

Mean squared difference in excitation mode loadings between the overall model and the model with a given sample omitted.

omitted

The sample (name if cube had names, integer if it didn't) that was omitted from a given model.

IMP

score.overall

Score values for the overall model.

score.predicted

Score values estimated from the loadings of the model missing a given sample.

factor

The component number.

omitted

The sample (name if cube had names, integer if it didn't) that was omitted from a given model.

References

\reference

Riu2003

See Also

feemparafac, feemcube

Examples

  data(feems)
  cube <- feemscale(feemscatter(cube, rep(14, 4)), na.rm = TRUE)
  # takes a long time; the stopping criterion is weaked for speed
  jk <- feemjackknife(cube, nfac = 3, ctol = 1e-4)
  # feemparafac methods should be able to use the environment and subset
  plot(jk$leaveone[[1]])
  plot(jk)
  plot(jk, 'IMP')
  plot(jk, 'RIP')
  head(coef(jk))

albatross documentation built on May 29, 2024, 9:10 a.m.