S3 methods for mdm objects

WARNING: These methods are experimental and must not be used in production. Their API is very likely to change in non-backwards-compatible ways over the next few weeks.

S3 methods for objects of class mdm and summary.mdm.

predict.mdm() predicts probabilities, classes, link scores, or all three from an mdm object. When newdata is a spectra object, the spectra are deconvoluted, aligned and snapped to the reference stored in the model before prediction. When newdata is a numeric matrix, it is used directly as the feature matrix.

print.mdm() prints a compact model summary.

coef.mdm() returns lasso coefficients.

plot.mdm() plots the lasso path.

summary.mdm() builds a compact summary list.

print.summary.mdm() prints formatted output for summary.mdm objects.

Usage

# S3 method for class 'mdm'
predict(
  object,
  newdata,
  type = c("all", "prob", "class", "link"),
  s = "lambda.min",
  nworkers = 1,
  verbosity = 1,
  ...
)

# S3 method for class 'mdm'
print(x, ...)

# S3 method for class 'mdm'
coef(object, ...)

# S3 method for class 'mdm'
plot(x, ...)

# S3 method for class 'mdm'
summary(object, ...)

# S3 method for class 'summary.mdm'
print(x, ...)

Arguments

object, x

A fitted mdm object (for predict, coef, summary, print and plot) or a summary.mdm object (for print.summary.mdm).

newdata

Spectra object or numeric feature matrix.

type

Prediction type, one of "all", "prob", "class", "link".

s

Regularization value for lasso predictions.

nworkers

Number of workers to deconvolute and align newdata.

verbosity

Integer verbosity level.

...

Passed to underlying methods where applicable.

Value

• predict: numeric vector of probabilities, classes, and/or link scores.

• print: invisibly returns x.

• coef: coefficient object from glmnet.

• plot: invisibly returns NULL.

• summary: object of class summary.mdm.

• print.summary.mdm: invisibly returns x.

Examples

m <- structure(
  list(
    model = NULL,
    ref = NULL,
    meta = list(npmax = 1000, nfit = 3, smit = 2, smws = 5,
                delta = 6.4, maxShift = 100, maxCombine = 50,
                combineMethod = 2)
  ),
  class = "mdm"
)
print(m)
#> metabodecon model (mdm)
#>   npmax:         1000
#>   nfit:          3
#>   smit:          2
#>   smws:          5
#>   delta:         6.4
#>   maxShift:      100
#>   maxCombine:    50
#>   combineMethod: 2
summary(m)
#> Summary of mdm
#>   npmax:         1000
#>   nfit:          3
#>   smit:          2
#>   smws:          5
#>   delta:         6.4
#>   maxShift:      100
#>   maxCombine:    50
#>   combineMethod: 2
#>   n_peaks:       0
#>   grid_rows:     0

if (FALSE) { # \dontrun{
  m <- cv_mdm(spectra, y, sfr = c(11, -2))
  predict(m, test_spectra, type = "prob")
  coef(m)
  plot(m)
} # }