Particle Swarm Optimization and regression analysis – I

Abstract Particle Swarm Optimization (PSO) is now widely used in many problems that require global optimization of high-dimensional and highly multi-modal functions. However, PSO has not yet seen widespread use in astronomical data analysis even though optimization problems in this field have become increasingly complex. In this two-part article, we first provide an overview of the PSO method in the concrete context of a ubiquitous problem in astronomy, namely, regression analysis. In particular, we consider the problem of optimizing the placement of knots in regression based on cubic splines (spline smoothing). The second part will describe an in-depth investigation of PSO in some realistic data analysis challenges.