Predictions of a Robust PCR Model

Predicts the responses of new observations with a model fitted by rpcr(), or computes their scores.

Usage

# S3 method for class 'specproc_rpcr'
predict(object, newdata, type = c("response", "scores"), ncomp = NULL, ...)

Arguments

object

An object returned by rpcr().

newdata

A numeric matrix or data frame with the same variables as the calibration data.

type

"response" (default) for the predicted responses, or "scores" for the scores and their score and orthogonal distances.

ncomp

With type = "response", the number of components of the predictions, from 1 to the kmax of the model. Default is the ncomp of the model. The models with fewer or more components use the same robust PCA (see rpcr()).

...

Not used.

Value

With type = "response", a numeric vector of predictions (one response) or a matrix with one column per response. With type = "scores", a tibble with the scores (Comp1, ...), the score distance sd and the orthogonal distance od of each observation.

See also

rpcr()

Author

Christian L. Goueguel

Examples

data(forageLIBS)
wl <- suppressWarnings(as.numeric(names(forageLIBS)))
spectra <- forageLIBS[which(wl > 380 & wl < 430)]
set.seed(1)
fit <- rpcr(spectra[1:300, ], forageLIBS$Ca[1:300], ncomp = 5)
head(predict(fit, spectra[301:368, ]))
#> [1] 0.4693860 0.3976267 0.6559014 0.5791613 0.7150952 0.3257995
head(predict(fit, spectra[301:368, ], type = "scores"))
#> # A tibble: 6 × 7
#>     Comp1  Comp2   Comp3  Comp4   Comp5    sd    od
#>     <dbl>  <dbl>   <dbl>  <dbl>   <dbl> <dbl> <dbl>
#> 1 -75682. -2806. -14836.  1082.   -36.5  3.23 5893.
#> 2 -61523. 16754. -16108.  1342. -1467.   3.61 7167.
#> 3 -25741. -1352.   3296. -4067. -6537.   2.43 5076.
#> 4 -47613. -3065.  -8407. -1544. -1743.   2.08 5455.
#> 5 -32271. -8880.    184. -5290. -4690.   2.44 4033.
#> 6 -50785.  -192.  -7612.  7918. -2650.   2.88 8824.