State estimation for temporal point processes

This paper is concerned with combined inference for point processes on the real line observed in a broken interval. For such processes, the classic history-based approach cannot be used. Instead, we adapt tools from sequential spatial point processes. For a range of models, the marginal and conditional distributions are derived. We discuss likelihood based inference as well as parameter estimation using the method of moments, conduct a simulation study for the important special case of renewal processes and analyse a data set collected by Diggle and Hawtin

A spectral mean for point sampled closed curves

We propose a spectral mean for closed curves described by sample points on its boundary subject to mis-alignment and noise. First, we ignore mis-alignment and derive maximum likelihood estimators of the model and noise parameters in the Fourier domain. We estimate the unknown curve by back-transformation and derive the distribution of the integrated squared error. Then, we model mis-alignment by means of a shifted parametric diffeomorphism and minimise a suitable objective function simultaneously over the unknown curve and the mis-alignment parameters. Finally, the method is illustrated on simulated data as well as on photographs of Lake Tana taken by astronauts during a Shuttle mission

Non-parametric indices of dependence between components for inhomogeneous multivariate random measures and marked sets

We propose new summary statistics to quantify the association between the components in coverage-reweighted moment stationary multivariate random sets and measures. They are defined in terms of the coverage-reweighted cumulant densities and extend classic functional statistics for stationary random closed sets. We study the relations between these statistics and evaluate them explicitly for a range of models. Unbiased estimators are given for all statistics and applied to simulated examples.Comment: Added examples in version

A J-function for inhomogeneous spatio-temporal point processes

We propose a new summary statistic for inhomogeneous intensity-reweighted moment stationary spatio-temporal point processes. The statistic is defined through the n-point correlation functions of the point process and it generalises the J-function when stationarity is assumed. We show that our statistic can be represented in terms of the generating functional and that it is related to the inhomogeneous K-function. We further discuss its explicit form under some specific model assumptions and derive a ratio-unbiased estimator. We finally illustrate the use of our statistic on simulated data

Summary statistics for inhomogeneous marked point processes

We propose new summary statistics for intensity-reweighted moment stationary marked point processes with particular emphasis on discrete marks. The new statistics are based on the n-point correlation functions and reduce to cross J- and D-functions when stationarity holds. We explore the relationships between the various functions and discuss their explicit forms under specific model assumptions. We derive ratio-unbiased minus sampling estimators for our statistics and illustrate their use on a data set of wildfires

Disentangling scale approaches in governance research: comparing monocentric, multilevel, and adaptive governance

The question of how to govern the multiscale problems in today’s network society is an important topic in the fields of public administration, political sciences, and environmental sciences. How scales are defined, studied, and dealt with varies substantially within and across these fields. This paper aims to reduce the existing conceptual confusion regarding scales by disentangling three representative approaches that address both governance and scaling: monocentric governance, multilevel governance, and adaptive governance. It does so by analyzing the differences in (1) underlying views on governing, (2) assumptions about scales, (3) dominant problem definitions regarding scales, and (4) preferred responses for dealing with multiple scales. Finally, this paper identifies research opportunities within and across these approaches

Near-infrared emission from sublimating dust in collisionally active debris disks

Hot exozodiacal dust is thought to be responsible for excess near-infrared (NIR) emission emanating from the innermost parts of some debris disks. The origin of this dust, however, is still a matter of debate. We test whether hot exozodiacal dust can be supplied from an exterior parent belt by Poynting-Robertson (P-R) drag, paying special attention to the pile-up of dust that occurs due to the interplay of P-R drag and dust sublimation. Specifically, we investigate whether pile-ups still occur when collisions are taken into account, and if they can explain the observed NIR excess. We compute the steady-state distribution of dust in the inner disk by solving the continuity equation. First, we derive an analytical solution under a number of simplifying assumptions. Second, we develop a numerical debris disk model that for the first time treats the complex interaction of collisions, P-R drag, and sublimation in a self-consistent way. From the resulting dust distributions we generate thermal emission spectra and compare these to observed excess NIR fluxes. We confirm that P-R drag always supplies a small amount of dust to the sublimation zone, but find that a fully consistent treatment yields a maximum amount of dust that is about 7 times lower than that given by analytical estimates. The NIR excess due this material is much smaller (<10^-3 for A-type stars with parent belts at >1 AU) than the values derived from interferometric observations (~10^-2). Pile-up of dust still occurs when collisions are considered, but its effect on the NIR flux is insignificant. Finally, the cross-section in the innermost regions is clearly dominated by barely bound grains.Comment: 18 pages, 10 figures, A&A accepte

Do scale frames matter? Scale frame mismatches in the decision making process of a 'mega farm' in a small Dutch village

Scale issues are an increasingly important feature of complex sustainability issues, but they are mostly taken for granted in policy processes. However, the scale at which a problem is defined as well as the scale at which it should be solved are potentially contentious issues. The framing of a problem as a local, regional, or global problem is not without consequences and influences processes of inclusion and exclusion. Little is known about the ways actors frame scales and the effect of different scale frames on decision making processes. This paper addresses the questions that different scale frames actors use and what the implications of scale frames are for policy processes. It does so by analyzing the scale frames deployed by different actors on the establishment of a so-called new mixed company or mega farm and the related decision making process in a Dutch municipality. We find that actors deploy different and conflicting scale frames, leading to scale frame mismatches. We conclude that scale frame mismatches play an important role in the stagnation of the decision making proces