Title: Contemplating Statistics: estimation and regression according to arc lengths

Date: Monday, 19 June 2017

Time: 09:00

Venue: Board room 3-44, Plant Sciences Complex, Hatfield Campus

RSVP: to [email protected] by Thursday, 15 June 2017

Enquiries: Prof Andriette Bekker at 012 420 2523 or [email protected]

Advances in computing have undoubtedly been one of the main catalysts in the formation of the discipline known as Statistics. A fundamental question addressed here is whether computing facilities, such as parallel or high performance computing, could assist in the development of methodologies that render stronger results, based on some predetermined optimality criterion. The candidate at the hand of which this enquiry is made, is the arc length of some statistical function. Estimation, goodness-of-fit, linear regression and non-linear regression, which may all be considered as central themes in Statistics, are revisited, and redefined in terms of this new measure. The results emanating from these arc length methodologies are obtained from simulation, as well as from real case studies, and contrasted with those obtained using their classical counterparts. Mathematical premises for the proposed methods are provided, together with the documentation accompanying the companion R package and the data utilised for the applications.