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Updates in Bayesian Filtering by Continuous Projections on a Manifold of Densities

In this paper, we develop a novel method for approximate continuous-discrete Bayesian filtering. The projection filtering framework is exploited to develop accurate approximations of posterior distributions within parametric classes of probability distributions. This is done by formulating an ordinary differential equation for the posterior distribution that has the prior as initial value and hits

Mixture representation of the Matérn class with applications in state space approximations and Bayesian quadrature

In this paper, the connection between the Matérn kernel and scale mixtures of squared exponential kernels is explored. It is shown that the Matérn kernel can be approximated by a finite scale mixture of squared exponential kernels through a quadrature approximation which in turn allows for (i) state space approximations of the Matérn kernel for arbitrary smoothness parameters using established sta

Continuous-discrete filtering and smoothing on submanifolds of euclidean space

In this paper the issue of filtering and smoothing in continuous discrete time is studied when the state variable evolves in some submanifold of Euclidean space, which may not have the usual Lebesgue measure. Formal expressions for prediction and smoothing problems are reviewed, which agree with the classical results except that the formal adjoint of the generator is different in general. These re

Joint Calibration of Inertial Sensors and Magnetometers using von Mises-Fisher Filtering and Expectation Maximization

Microelectromechanical-systems-based inertial sensors and magnetometers are low-cost, off-the-shelf sensors that are widely used in both consumer and industrial applications. However, these sensors suffer from biases and effects such as axis misalignment or scale errors, which require careful system design and periodic sensor calibration. In this paper, we propose a fast calibration method for joi

Non-Linear Continuous-Discrete Smoothing by Basis Function Expansions of Brownian Motion

This paper is concerned with inferring the state of a Itô stochastic differential equation (SDE) from noisy discrete-time measurements. The problem is approached by considering basis function expansions of Brownian motion, that as a consequence give approximations to the underlying stochastic differential equation in terms of an ordinary differential equation with random coefficients. This allows

Vad gör djuren när de blir rädda?

Alla blir vi rädda någon gång, både människor och djur. Ibland är det samma saker som skrämmer och ibland är det något helt annat som djuren tycker är läskigt.Vad gör djuren när de blir skrämda? Kanske gömmer de sig? Försöker de springa därifrån? Eller försöker djuren lura den som skräms att titta åt ett helt annat håll? Ska vi kolla hur djuren gör?Vad gör djuren när de blir rädda? är en bok som g

Similarities, differences, and tendencies of water damage in the Nordic countries

This extended abstract compiles statistics and information regarding the process of gathering water damage statistics. A questionnaire wasused to determine similarities, differences, and tendencies in the water damage statistics, in the Nordic countries Sweden, Norway, Denmark,Finland and Iceland. The study aimed to answer what lessons were learned and what knowledge could be shared between the No

Litigation Finance and the Assetization of International Investment Arbitration

Third Party Funding (TPF) is presented as a tool to help fund the cost of expensive litigation. In the context of Investment Arbitration, however, TPF has instead led to the commodification of justice, and raises concerns around its assetization. Arbitration often comes at a net loss for States, and the extraordinary expenditures required my pique the interest of third party funders who wish to pr

Spatiotemporal Analysis of Nodding Syndrome in Northern Uganda 1990-2014

The emergence of nodding syndrome (NS) in Northern Uganda has generated controversial views with respect to patterns, natural history, and aetiology of the disease which is yet unknown. This study explored spatial patterns of NS using spatial-temporal methods to establish its clustering patterns across both space and time. Village and year of NS onset for individual patients between the years 1990

Half-panel jackknife estimation for dynamic panel models

This paper extends the half-panel jackknife (HPJ) estimator to GMM models with fixed effects. The Monte Carlo results show that the HPJ significantly reduces finite-sample bias for both the difference and system GMM estimators of the dynamic panel model.

Shifting Gears : Automated Driving on the Eve of Autonomous Drive

The compelling images and promises attached to autonomous drive vehicles can easily create an impression that one can speak of a radical distinction between a self-driving future and a manual-driving present. Yet today’s drivers can already refer to their everyday driving as being experienced as though on ‘auto-pilot’, in which they are able to drive their cars while lost in things such as daydrea