103,495 research outputs found
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Evaluating the impact of healthcare education: Approaches and challenges
Modeling and Estimation for Self-Exciting Spatio-Temporal Models of Terrorist Activity
Spatio-temporal hierarchical modeling is an extremely attractive way to model
the spread of crime or terrorism data over a given region, especially when the
observations are counts and must be modeled discretely. The spatio-temporal
diffusion is placed, as a matter of convenience, in the process model allowing
for straightforward estimation of the diffusion parameters through Bayesian
techniques. However, this method of modeling does not allow for the existence
of self-excitation, or a temporal data model dependency, that has been shown to
exist in criminal and terrorism data. In this manuscript we will use existing
theories on how violence spreads to create models that allow for both
spatio-temporal diffusion in the process model as well as temporal diffusion,
or self-excitation, in the data model. We will further demonstrate how Laplace
approximations similar to their use in Integrated Nested Laplace Approximation
can be used to quickly and accurately conduct inference of self-exciting
spatio-temporal models allowing practitioners a new way of fitting and
comparing multiple process models. We will illustrate this approach by fitting
a self-exciting spatio-temporal model to terrorism data in Iraq and demonstrate
how choice of process model leads to differing conclusions on the existence of
self-excitation in the data and differing conclusions on how violence is
spreading spatio-temporally
An Extended Laplace Approximation Method for Bayesian Inference of Self-Exciting Spatial-Temporal Models of Count Data
Self-Exciting models are statistical models of count data where the
probability of an event occurring is influenced by the history of the process.
In particular, self-exciting spatio-temporal models allow for spatial
dependence as well as temporal self-excitation. For large spatial or temporal
regions, however, the model leads to an intractable likelihood. An increasingly
common method for dealing with large spatio-temporal models is by using Laplace
approximations (LA). This method is convenient as it can easily be applied and
is quickly implemented. However, as we will demonstrate in this manuscript,
when applied to self-exciting Poisson spatial-temporal models, Laplace
Approximations result in a significant bias in estimating some parameters. Due
to this bias, we propose using up to sixth-order corrections to the LA for
fitting these models. We will demonstrate how to do this in a Bayesian setting
for Self-Exciting Spatio-Temporal models. We will further show there is a
limited parameter space where the extended LA method still has bias. In these
uncommon instances we will demonstrate how a more computationally intensive
fully Bayesian approach using the Stan software program is possible in those
rare instances. The performance of the extended LA method is illustrated with
both simulation and real-world data
Recommended from our members
Evaluating the impact of healthcare education: the challenges and a way forward
Radio observations of the massive stellar cluster Westerlund 1
High-dynamic range radio observations of Westerlund 1 are presented that
detect a total of 21 stars in the young massive stellar cluster, the richest
population of radio emitting stars known for any young massive galactic cluster
in the Galaxy. We will discuss some of the more remarkable objects, including
the highly radio luminous supergiant B[e] star W9, with an estimated mass-loss
rate ~10^{-3} solarmass/yr, comparable to that of eta Carina, along with the
somewhat unusual detection of thermal emission from almost all the cool red
supergiants and yellow hypergiants. There is strong supporting evidence from
X-ray observations that each of the WR stars with radio emission are likely to
be colliding-wind binariesComment: To appear in the proceedings of "Massive Stars: Fundamental
Parameters and Circumstellar Interactions". 2 pages, 1 figur
Biochemical, endocrine, and hematological factors in human oxygen tolerance extension: Predictive studies 6
The Predictive Studies VI (Biochemical, endocrine, and hematological factors in human oxygen tolerance extension) Program consisted of two related areas of research activity, integrated in design and performance, that were each based on an ongoing analysis of human organ oxygen tolerance data obtained for the continuous oxygen exposures of the prior Predictive Studies V Program. The two research areas effectively blended broad investigation of systematically varied intermittent exposure patterns in animals with very selective evaluation of specific exposure patterns in man
Disc loss and renewal in A0535+26
This paper presents observations of the Be/X-ray binary system A0535+26
revealing the first observed loss of its circumstellar disc, demonstrated by
the loss of its JHK infrared excess and optical/IR line emission. However
optical/IR spectroscopy reveals the formation of a new inner disc with
significant density and emission strength at small radii; the disc has proven
to be stable over 5 months in this intermediate state.Comment: 4 pages, 4 figures, accepted by MNRAS, uses mn.st
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