Computes the net analyte signal, selectivity and predicted concentration
of new samples with a model fitted by nas().
Usage
# S3 method for class 'specproc_nas'
predict(object, newdata, ...)Arguments
- object
An object returned by
nas().- newdata
A numeric matrix or data frame of new spectra, with the same variables as the calibration spectra.
- ...
Not used.
Value
A tibble with one row per new sample and columns nas,
selectivity, predicted and, if the model has a noise level, snr.
Examples
data(forageLIBS)
wl <- suppressWarnings(as.numeric(names(forageLIBS)))
spectra <- forageLIBS[which(wl > 760 & wl < 780)] # the K I resonance lines
cal <- 1:300
fit <- nas(spectra[cal, ], forageLIBS$K[cal], ncomp = 3)
head(predict(fit, spectra[-cal, ]))
#> # A tibble: 6 × 3
#> nas selectivity predicted
#> <dbl> <dbl> <dbl>
#> 1 -144. 0.00575 1.98
#> 2 522. 0.0144 2.15
#> 3 764. 0.104 2.21
#> 4 -61.3 0.00227 2.00
#> 5 25.4 0.000857 2.02
#> 6 -1329. 0.140 1.68