v. 0.12.0

This release is mostly about preprocessing - added some new methods, improved the existent once and implemented a possibility to combine preprocessing methods together (including parameter values) and apply them all together in a correct sequence. See preprocessing section in the tutorials for details

New features and improvements

• method prep.norm() for normalization of spectra (or any other signals) is more versatile now and supports normalization to unit sum, length, area, to height or area under internal standard peak, and SNV. SNV via prop.snv() is still supported for compatibility.

• prep.savgol() has been rewritten to fix a minor bug when first derivative was inverted, but also to make the handling of the edge points better. See details in help text for the function and in the tutorial.

• added a new method prep.transform() which can be used for transformation of values of e.g. response variable to handle non-linearity.

• added a new method prep.varsel() which makes possible to select particular variables as a part of preprocessing framework. For example you can apply baseline correction, normalization and noise suppression to the whole spectra and after that select only a particular part for modelling.

• added new method prep() which let you to combine several preprocessing methods and their parameters into a list and use e.g. it as a part of model.

Bug fixes

• fixed a bug in mcrals() which in rare occasions could lead to a wrong error message.

• fixed a bug when attribute yaxis.value was used as ylab when creating line and bar plots.

• fixed an earlier reported issue with plotXYResiduals (#100)