Archive for Warwickshire

amber warning

Posted in Statistics with tags , , , , , , on December 10, 2017 by xi'an

Just saw this severe Met warning of snow over Warwickshire and neighbouring counties… The campus is indeed covered with snow, but not that heavily. Yet. (It is comparatively mild in Austin, Texas, even though the icy wind turned my fingers to iciles during my morning run there!)

Amber warning of snow

From: 0810 on Sun 10 December
To: 1800 on Sun 10 December
Updated 6 hours ago Active

A spell of heavy snow is likely over parts of Wales, the Midlands and parts of Northern and Eastern England on Sunday.

Road, rail and air travel delays are likely, as well as stranding of vehicles and public transport cancellations. There is a good chance that some rural communities could become cut off.This is an update to extend the warning area as far south as Gloucestershire, Wiltshire, Oxfordshire, Buckinghamshire, Hertfordshire and Essex.

importance demarginalising

Posted in Books, Kids, pictures, Running, Statistics, Travel, University life with tags , , , , , on November 27, 2017 by xi'an

A question on X validated gave me minor thought fodder for my crisp pre-dawn run in Warwick the other week: if one wants to use importance sampling for a variable Y that has no closed form density, but can be expressed as the transform (marginal) of a vector of variables with closed form densities, then, for Monte Carlo approximations, the problem can be reformulated as the computation of an integral of a transform of the vector itself and the importance ratio is given by the ratio of the true density of the vector over the density of the simulated vector. No Jacobian involved.

Avon river

Posted in pictures, Running, Travel with tags , , , , , , , , on June 3, 2016 by xi'an

bridge upon the Avon river, Stoneleigh, Warwickshire, May 31, 2016

Stoneleigh Abbey

Posted in pictures, Running, Travel with tags , , , , , , on June 2, 2016 by xi'an

another glorious sunrise in Warwickshire

Posted in pictures, Running, Travel, University life with tags , , , , , , , on April 30, 2016 by xi'an

maths house, University of Warwick

Posted in pictures, Travel, University life with tags , , , , , , on July 16, 2015 by xi'an

mthus

probabilistic numerics

Posted in pictures, Running, Statistics, Travel, University life with tags , , , , , , , , , , , , , , , on April 27, 2015 by xi'an

sunwar2I attended an highly unusual workshop while in Warwick last week. Unusual for me, obviously. It was about probabilistic numerics, i.e., the use of probabilistic or stochastic arguments in the numerical resolution of (possibly) deterministic problems. The notion in this approach is fairly Bayesian in that it makes use to prior information or belief about the quantity of interest, e.g., a function, to construct an usually Gaussian process prior and derive both an estimator that is identical to a numerical method (e.g., Runge-Kutta or trapezoidal integration) and uncertainty or variability around this estimator. While I did not grasp much more than the classy introduction talk by Philipp Hennig, this concept sounds fairly interesting, if only because of the Bayesian connection, and I wonder if we will soon see a probability numerics section at ISBA! More seriously, placing priors on functions or functionals is a highly formal perspective (as in Bayesian non-parametrics) and it makes me wonder how much of the data (evaluation of a function at a given set of points) and how much of the prior is reflected in the output [variability]. (Obviously, one could also ask a similar question for statistical analyses!)  For instance, issues of singularity arise among those stochastic process priors.

Another question that stemmed from this talk is whether or not more efficient numerical methods can derived that way, in addition to recovering the most classical ones. Somewhat, somehow, given the idealised nature of the prior, it feels like priors could be more easily compared or ranked than in classical statistical problems. Since the aim is to figure out the value of an integral or the solution to an ODE. (Or maybe not, since again almost the same could be said about estimating a normal mean.)