pkdecomp: Decomposition of peaks for the whole data set
In diffractometry: Baseline Identification and Peak Decomposition for x-Ray Diffractograms

Description Usage Arguments Details Value Author(s) References See Also Examples

Calculates decompositions of peaks for the whole diffractogram

1 2	pkdecomp(baslfit,intnum=0, alpha=0.1, maxiter1=500, maxiter=10000, hmax=5, maxsolutions=3,heterosk=TRUE,baselim=c(0.05,5),dispers=1)

`baslfit`	Output of `baselinefit`
`intnum`	Vector of numbers of intervals. If `intnum = 0`, all intervals are used
`alpha`	Test level for residual criterion
`maxiter1`	Number of attempts to fit a model with 1 component
`maxiter`	Number of attempts to fit a model with k > 1 components
`hmax`	Maximum number of components
`maxsolutions`	Number of solutions with k components
`heterosk`	If `TRUE`, the estimate of noise level given in `baslfit` is used (default); otherwise noise level is taken to be proportional to signal height
`baselim`	Limits for changes in the baseline estimate; first component is given in percent of the baseline height, second in counts/2theta
`dispers`	Additional dispersion factor; not used if `heterosk==T`

Calls pkdecompint to decompose the peaks found by baselinefit into Pearson Type VII kernels. For every interval, first one kernel is tried. The number of kernels is increased until either a solution accepted by the residual criterion is found or the maximum number of kernels hmax is reached. After a solution is accepted, for maxsolutions greater than 1, further decompositions with the same number of kernels can be produced.

A vector of lists as given by pkdecompint

T. Mildenberger; Algorithm for residual criterion by T. Bernholt and T. Hofmeister

P.L. Davies, U. Gather, M. Meise, D. Mergel, T. Mildenberger (2008): "Residual based localization and quantification of peaks in x-ray diffractograms", Annals of Applied Statistics, Vol. 2, No. 3, 861-886.. http://www.statistik.tu-dortmund.de/fileadmin/user_upload/Lehrstuehle/MSind/Publikationen/2008/2008_-_Davies_Gather_Meise_Mergel_Mildenberger_-_Residual_based_localization_and_quantification_of_peaks_in_x-ray_diffractograms.pdf

T. Bernholt and T. Hofmeister (2006): "An algorithm for a generalized maximum subsequence problem", in: J. Correa, A. Hevia, M. Kiwi (editors), "Latin 2006: Theoretical Informatics", volume 3887 of Lecture notes in Computer Science, pages 178-189, Berlin, Heidelberg. Springer Verlag

diffractogram, baselinefit, pkdecompint

## Decomposition of data in peak interval into two components

set.seed(0)

par(mfrow=c(2,1))

data(indiumoxide)
indox<-indiumoxide[1901:2400,]
base<-baselinefit(indox)

ind<-c(base$indlsep[1],base$indrsep[1])

plot(indox[ind[1]:ind[2],1], base$baseline$peaks[ind[1]:ind[2]],xlab="",ylab="")

pks<-pkdecomp(base,intnum=1,maxsolutions=1,maxiter1=50,maxiter=250)

lines(indox[ind[1]:ind[2],1],pks[[2]]$fit,col="red")
plot(indox[ind[1]:ind[2],1],pks[[2]]$fitpk[1,],ylim=c(0,1800),type="l",xlab="",ylab="")
lines(indox[ind[1]:ind[2],1],pks[[2]]$fitpk[2,])