An Introduction to the 'Special Volume Spectroscopy and Chemometrics in R'

This special volume collates ten issues under the rubric "Spectroscopy and Chemometrics in R". In so doing, it provides an overview of the breadth, depth and state of the art of R-based software projects for spectroscopy and chemometrics applications. Just as the authors have contributed to R their documentation and source code, so has R contributed to the quality, standardization and dissemination of their software, as this volume attests. We hope that the volume is inspiring to both computational statisticians interested in applications of their methodologies and to spectroscopists or chemometricians in need of solutions to their data analysis problems.

TIMP: An R package for modeling multi-way spectroscopic measurements

TIMP is an R package for modeling multiway spectroscopic measurements. The package allows for the simultaneous analysis of datasets collected under different experimental conditions in terms of a wide variety of parametric models. Models arising in spectroscopy data analysis often have some parameters that are intrinstically nonlinear, and some parameters that are conditionally linear on estimates of the nonlinear parameters. TIMP fits such separable nonlinear models using partitioned variable projection, a variant of the variable projection algorithm that is described here for the first time. The of the partitioned variable projection algorithm allows fitting many models for spectroscopy datasets using much less memory as compared to under the standard variable projection algorithm that is implemented in nonlinear optimization routines (e.g., the plinear option of the R function nls), as is shown here. An overview of modeling with TIMP is also given that includes several case studies in the application of the package

Global and target analysis of time-resolved spectra

AbstractIn biological/bioenergetics research the response of a complex system to an externally applied perturbation is often studied. Spectroscopic measurements at multiple wavelengths are used to monitor the kinetics. These time-resolved spectra are considered as an example of multiway data. In this paper, the methodology for global and target analysis of time-resolved spectra is reviewed. To fully extract the information from the overwhelming amount of data, a model-based analysis is mandatory. This analysis is based upon assumptions regarding the measurement process and upon a physicochemical model for the complex system. This model is composed of building blocks representing scientific knowledge and assumptions. Building blocks are the instrument response function (IRF), the components of the system connected in a kinetic scheme, and anisotropy properties of the components. The combination of a model for the kinetics and for the spectra of the components results in a more powerful spectrotemporal model. The model parameters, like rate constants and spectra, can be estimated from the data, thus providing a concise description of the complex system dynamics. This spectrotemporal modeling approach is illustrated with an elaborate case study of the ultrafast dynamics of the photoactive yellow protein