Honoring the Lion: A Festschrift for Jan de Leeuw

This special volume celebrates the 20th anniversary of the Journal of Statistical Software (JSS) and is a Festschrift for its founding editor Jan de Leeuw. Jan recently retired from his long-held position as founding chair of the Department of Statistics at the University of California, Los Angeles. The contributions to this special volume look back at some of his research interests and accomplishments during the half-century that he has been active in psychometrics and statistics. In this introduction, the guest editors also reminisce on their own first encounters with Jan, ten years ago. Since that time JSS has solidified its place as a leading journal of computational statistics, a fact that has a lot to do with Jan's stewardship. We include a brief history of JSS

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.

DEoptim: An R Package for Global Optimization by Differential Evolution

This article describes the R package DEoptim, which implements the differential evolution algorithm for global optimization of a real-valued function of a real-valued parameter vector. The implementation of differential evolution in DEoptim interfaces with C code for efficiency. The utility of the package is illustrated by case studies in fitting a Parratt model for X-ray reflectometry data and a Markov-switching generalized autoregressive conditional heteroskedasticity model for the returns of the Swiss Market Index.

DEoptim: An R Package for Global Optimization by Differential Evolution

This article describes the R package DEoptim, which implements the differential evolution algorithm for global optimization of a real-valued function of a real-valued parameter vector. The implementation of differential evolution in DEoptim interfaces with C code for efficiency. The utility of the package is illustrated by case studies in fitting a Parratt model for X-ray reflectometry data and a Markov-switching generalized autoregressive conditional heteroskedasticity model for the returns of the Swiss Market Index

FluxSimulator: An R Package to Simulate Isotopomer Distributions in Metabolic Networks

The representation of biochemical knowledge in terms of fluxes (transformation rates) in a metabolic network is often a crucial step in the development of new drugs and efficient bioreactors. Mass spectroscopy (MS) and nuclear magnetic resonance spectroscopy (NMRS) in combination with ^13C labeled substrates are experimental techniques resulting in data that may be used to quantify fluxes in the metabolic network underlying a process. The massive amount of data generated by spectroscopic experiments increasingly requires software which models the dynamics of the underlying biological system. In this work we present an approach to handle isotopomer distributions in metabolic networks using an object-oriented programming approach, implemented using S4 classes in R. The developed package is called FluxSimulator and provides a user friendly interface to specify the topological information of the metabolic network as well as carbon atom transitions in plain text files. The package automatically derives the mathematical representation of the formulated network, and assembles a set of ordinary differential equations (ODEs) describing the change of each isotopomer pool over time. These ODEs are subsequently solved numerically. In a case study FluxSimulator was applied to an example network. Our results indicate that the package is able to reproduce exact changes in isotopomer compositions of the metabolite pools over time at given flux rates.

Fluorescence Lifetime Imaging Microscopy (FLIM) Data Analysis with TIMP

Fluorescence Lifetime Imaging Microscopy (FLIM) allows fluorescence lifetime images of biological objects to be collected at 250 nm spatial resolution and at (sub-)nanosecond temporal resolution. Often n_comp kinetic processes underlie the observed fluorescence at all locations, but the intensity of the fluorescence associated with each process varies per-location, i.e., per-pixel imaged. Then the statistical challenge is global analysis of the image: use of the fluorescence decay in time at all locations to estimate the n_comp lifetimes associated with the kinetic processes, as well as the amplitude of each kinetic process at each location. Given that typical FLIM images represent on the order of 10^2 timepoints and 10^3 locations, meeting this challenge is computationally intensive. Here the utility of the TIMP package for R to solve parameter estimation problems arising in FLIM image analysis is demonstrated. Case studies on simulated and real data evidence the applicability of the partitioned variable projection algorithm implemented in TIMP to the problem domain, and showcase options included in the package for the visual validation of models for FLIM data.

Differential Evolution (DEoptim) for Non-Convex Portfolio Optimization

The R package DEoptim implements the differential evolution algorithm. This algorithm is an evolutionary technique similar to genetic algorithms that is useful for the solution of global optimization problems. In this note we provide an introduction to the package and demonstrate its utility for financial applications by solving a non-convex portfolio optimization problem

DEoptim: An R Package for Global Optimization by Differential Evolution

This article describes the R package DEoptim which implements the differential evolution algorithm for the global optimization of a real-valued function of a real-valued parameter vector. The implementation of differential evolution in DEoptim interfaces with C code for efficiency. The utility of the package is illustrated via case studies in fitting a Parratt model for X-ray reflectometry data and a Markov-Switching Generalized AutoRegressive Conditional Heteroskedasticity (MSGARCH) model for the returns of the Swiss Market Index