1,839 research outputs found
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
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 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
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
Predicting Clinical Outcome in Children with ADHD:Is there a Role for Neurocognitive Functioning?
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
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