R: Fits a calibration model for soil spectroscopy

fit.SpectraModel-method {soil.spec}

R Documentation

Fits a calibration model for soil spectroscopy

Description

Fits a calibration model that can be used to convert absorbances to soil properties. Implements the "plsr" function available from the pls package.

Usage

 
## S4 method for signature 'formula,SpectraPoints,data.frame'
fit(formulaString, sampled, reference, 
   idcol = "SAMPLEID", ab.r = get("MIR", envir=spec.opts), 
   CO2.band = get("CO2.band", envir=spec.opts), ncomp, ncomp.max=15, 
   repl = 5, segment.type = "interleaved", prefix = "X", ...)
## S4 method for signature 'list,SpectraPoints,data.frame'
fit(formulaString, sampled, reference, ...)

Arguments

`formulaString`	`"formula"`; formula string
`sampled`	`"SpectraPoints"`; absorbances
`reference`	`"data.frame"`; reference values estimated in laboratory using at the order of magnitude more precise technique
`idcol`	`"character"`; column with sample IDs
`ab.r`	`"numeric"`; natural range of wavenumbers of interest
`CO2.band`	`"numeric"`; range of wavenumbers for the CO2 band
`ncomp`	`"integer"`; number of components (if not specified will be determined using cross-validation)
`ncomp.max`	`"integer"`; maximum number of components to be used for model fitting
`repl`	`"integer"`; number of repetitions for `"pls::plsr"`
`segment.type`	`"character"`; segment type for `"pls::plsr"`
`prefix`	`"character"`; default prefix to be added to the band names
`...`	other optional arguments

Details

Returns an object of class "SpectraModel", which contains slots: (1) "variable" (variable name according to the global soil data registry), (2) "Space" (3D space defined by the 1–3 principal components for absorbances), and (3) "model" (fitted model; usually of type pls::plsr and as an output from the partial least squares regression). Fitting models for large data sets can be time and memory consuming.

Author(s)

Andrew Sila and Tomislav Hengl

References

Mevik, B.-H., Wehrens, R. (2007) The pls Package: Principal Component and Partial Least Squares Regression in R. Journal of Statistical Software 18(2), 1-24.
Africa Soil Information Service (http://africasoils.net)

Examples

## Not run: 
## build a callibration model using AfSIS data:
library(plyr)
library(sp)
library(rgdal)

data(afss)
afss.tbl <- join(afss$sites, afss$horizons)
con <- url("http://gsif.isric.org/lib/exe/fetch.php?media=afss.spec.rda")
load(con)
afss.spec.ab <- Spectra(samples=data.frame(SAMPLEID=afss.spec$SAMPLEID, 
   MID="ICR_SOIL", DateTime=Sys.time()), ab=afss.spec)
sel.r <- !afss.tbl$LONWGS84==100
sp <- data.frame(afss.tbl[sel.r,c("LONWGS84","LATWGS84")])
coordinates(sp) <- ~LONWGS84+LATWGS84
proj4string(sp) <- CRS("+proj=longlat")
attr(sp@coords, "dimnames")[[1]] <- afss.tbl$SAMPLEID[sel.r]
## extend to SprectraPoints:
afss.spec.sp <- SpectraPoints(Spectra=afss.spec.ab, sp=sp)
## select bands of interest:
cutspec <- c(600,2350.8,2379.8,4000)
col.no <- sapply(names(afss.spec.sp@data@ab)[-1], 
   function(x){as.numeric(strsplit(x, "X")[[1]][2])})
sel <- col.no>cutspec[1] & col.no<cutspec[2] | 
       col.no>cutspec[3] & col.no<cutspec[4]
summary(sel)
formulaString <- as.formula(paste("na.omit(log(ORCDRC)) ~ ", 
   paste(names(afss.spec.sp@data@ab[-1])[sel], collapse="+")))
m.ORC <- fit(formulaString, sampled=afss.spec.sp, reference=afss.tbl) 
str(m.ORC)

## End(Not run)
## this model, in fact, is included in the package:
data(m.ORCCNS)
str(m.ORCCNS)

[Package soil.spec version 0.2.0 Index]