Parametric Time Warping
Trend estimation with asymmetric least squares
Baseline Correction using asymmetric least squares
Identification of optimal reference
Calculation of warping coefficients when applying more than one warpin...
Correction for warping coefficients when using zeropadding
Chromatogram selection using the CODA algorithm
Smoothing with a finite difference penalty
Conversion between peak lists from hyphenated MS (LCMS, GCMS, ...) dat...
Pad matrix with zeros
Plot a ptw object
Prediction of warped signals
tools:::Rd_package_title("ptw")
Parametric Time Warping
Calculate RMS or WCC values on a grid
Quality criteria for comparing patterns with shifts
Select traces from a data set according to several criteria
Transform time according to a given warping function
Weighted auto- and cross-correlation measures
Weighted Whittaker smoothing with a first order finite difference pena...
Weighted Whittaker smoothing with a second order finite difference pen...
Parametric Time Warping aligns patterns, i.e. it aims to put corresponding features at the same locations. The algorithm searches for an optimal polynomial describing the warping. It is possible to align one sample to a reference, several samples to the same reference, or several samples to several references. One can choose between calculating individual warpings, or one global warping for a set of samples and one reference. Two optimization criteria are implemented: RMS (Root Mean Square error) and WCC (Weighted Cross Correlation). Both warping of peak profiles and of peak lists are supported. A vignette for the latter is contained in the inst/doc directory of the source package - the vignette source can be found on the package github site.