Exact Bayesian curve fitting and signal segmentation.

We consider regression models where the underlying functional relationship between the response and the explanatory variable is modeled as independent linear regressions on disjoint segments. We present an algorithm for perfect simulation from the posterior distribution of such a model, even allowing for an unknown number of segments and an unknown model order for the linear regressions within each segment. The algorithm is simple, can scale well to large data sets, and avoids the problem of diagnosing convergence that is present with Monte Carlo Markov Chain (MCMC) approaches to this problem. We demonstrate our algorithm on standard denoising problems, on a piecewise constant AR model, and on a speech segmentation problem

Overcoming the factors inhibiting the mainstreaming of gender into spatial planning policy in the United Kingdom

This paper investigates why gender is not being effectively mainstreamed into the work of local planning authorities in the UK. It discusses means whereby this reluctance might be overcome. Research undertaken for the Royal Town Planning Institute is drawn upon to illustrate the situation. Whilst generic mainstreaming is widespread, it predominantly relates to personnel matters and social policy issues; but there is little evidence of the mainstreaming of gender issues into spatial policy. Factors that hinder progress are identified at central and local government levels. Drawing on principles from a gender mainstreaming toolkit, developed as part of the research, key stages and components of the planning process are identified through which gender might be more successfully mainstreamed into substantive spatial policy. © 2005 The Editors of Urban Studies