Andreas Ipsen

TL;DR: This paper discusses and applies an ABC method based on sequential Monte Carlo (SMC) to estimate parameters of dynamical models and develops ABC SMC as a tool for model selection; given a range of different mathematical descriptions, it is able to choose the best model using the standard Bayesian model selection apparatus.

TL;DR: More robust SLIM designs that reduce the race track effect while maximizing ion transmission are reported, and the dynamic switching of ions into orthogonal channels was also evaluated both using SIMION ion trajectory simulations and experimentally.

TL;DR: A new algorithm is proposed for identifying related parent−fragment pairs and for distinguishing these from signals due to unrelated compounds by means of a hypothesis test based on the distribution of the recorded ion counts, and thereby provides a statistically rigorous measure of the uncertainty involved in the classification problem.

TL;DR: This article presents a new approach to the treatment of such calculations, which involves arranging and manipulating the isotope patterns of distinct elements as multidimensional data structures that enables the use of the multiddimensional Fourier transform to calculate isotopes patterns with an accuracy that is limited only by the errors of floating point arithmetic.

TL;DR: A method for constructing confidence regions for the isotopic abundance patterns based on the fundamental distribution of the ion arrivals is presented and it is argued that further developments in the ability to characterize the data mathematically could enable much more powerful statistical analyses.