Scores and Distances of New Observations

Projects new observations onto a robust PCA model fitted by robpca(), rospca() or macropca(), and computes their score and orthogonal distances with the cut-offs of the calibration data.

Usage

# S3 method for class 'specproc_macropca'
predict(object, newdata, ...)

# S3 method for class 'specproc_cellpca'
predict(object, newdata, ...)

# S3 method for class 'specproc_robpca'
predict(object, newdata, ...)

Arguments

object

An object returned by robpca(), rospca() or macropca().

newdata

A numeric matrix or data frame with the same variables as the calibration data. For macropca(), missing values are allowed.

...

Not used.

Value

A tibble with the scores (PC1, ..., PCk), the score distance sd, the orthogonal distance od and the outlier_type of each new observation.

See also

plot_outlier_map(), which can display new observations.

Examples

data(forageLIBS)
wl <- suppressWarnings(as.numeric(names(forageLIBS)))
spectra <- forageLIBS[which(wl > 760 & wl < 780)]  # the K I resonance lines
set.seed(1)
fit <- robpca(spectra[1:300, ])
head(predict(fit, spectra[301:368, ]))
#> # A tibble: 6 × 4
#>       PC1    sd     od outlier_type      
#>     <dbl> <dbl>  <dbl> <fct>             
#> 1 -23113. 1.06   6527. regular           
#> 2 -33447. 1.53  10935. orthogonal outlier
#> 3  -4303. 0.197  4341. regular           
#> 4 -25272. 1.16   5235. regular           
#> 5 -27946. 1.28   5746. regular           
#> 6  -3636. 0.167  6703. regular