1,080 research outputs found
Indefinitely Oscillating Martingales
We construct a class of nonnegative martingale processes that oscillate
indefinitely with high probability. For these processes, we state a uniform
rate of the number of oscillations and show that this rate is asymptotically
close to the theoretical upper bound. These bounds on probability and
expectation of the number of upcrossings are compared to classical bounds from
the martingale literature. We discuss two applications. First, our results
imply that the limit of the minimum description length operator may not exist.
Second, we give bounds on how often one can change one's belief in a given
hypothesis when observing a stream of data.Comment: ALT 2014, extended technical repor
Deformed Gaussian Orthogonal Ensemble description of Small-World networks
The study of spectral behavior of networks has gained enthusiasm over the
last few years. In particular, Random Matrix Theory (RMT) concepts have proven
to be useful. In discussing transition from regular behavior to fully chaotic
behavior it has been found that an extrapolation formula of the Brody type can
be used. In the present paper we analyze the regular to chaotic behavior of
Small World (SW) networks using an extension of the Gaussian Orthogonal
Ensemble. This RMT ensemble, coined the Deformed Gaussian Orthogonal Ensemble
(DGOE), supplies a natural foundation of the Brody formula. SW networks follow
GOE statistics till certain range of eigenvalues correlations depending upon
the strength of random connections. We show that for these regimes of SW
networks where spectral correlations do not follow GOE beyond certain range,
DGOE statistics models the correlations very well. The analysis performed in
this paper proves the utility of the DGOE in network physics, as much as it has
been useful in other physical systems.Comment: Replaced with the revised version, accepted for publication in Phys.
Rev.
Transfer Entropy as a Log-likelihood Ratio
Transfer entropy, an information-theoretic measure of time-directed
information transfer between joint processes, has steadily gained popularity in
the analysis of complex stochastic dynamics in diverse fields, including the
neurosciences, ecology, climatology and econometrics. We show that for a broad
class of predictive models, the log-likelihood ratio test statistic for the
null hypothesis of zero transfer entropy is a consistent estimator for the
transfer entropy itself. For finite Markov chains, furthermore, no explicit
model is required. In the general case, an asymptotic chi-squared distribution
is established for the transfer entropy estimator. The result generalises the
equivalence in the Gaussian case of transfer entropy and Granger causality, a
statistical notion of causal influence based on prediction via vector
autoregression, and establishes a fundamental connection between directed
information transfer and causality in the Wiener-Granger sense
On stochasticity in nearly-elastic systems
Nearly-elastic model systems with one or two degrees of freedom are
considered: the system is undergoing a small loss of energy in each collision
with the "wall". We show that instabilities in this purely deterministic system
lead to stochasticity of its long-time behavior. Various ways to give a
rigorous meaning to the last statement are considered. All of them, if
applicable, lead to the same stochasticity which is described explicitly. So
that the stochasticity of the long-time behavior is an intrinsic property of
the deterministic systems.Comment: 35 pages, 12 figures, already online at Stochastics and Dynamic
Optimistic Agents are Asymptotically Optimal
We use optimism to introduce generic asymptotically optimal reinforcement
learning agents. They achieve, with an arbitrary finite or compact class of
environments, asymptotically optimal behavior. Furthermore, in the finite
deterministic case we provide finite error bounds.Comment: 13 LaTeX page
Media coverage and public understanding of sentencing policy in relation to crimes against children
This research examines how the media report on sentences given to those who commit serious crimes against children and how this impacts on public knowledge and attitudes. Three months of press and television coverage were analysed in order to establish the editorial lines that are taken in different sections of the media and how they are promoted by selective reporting of sentencing. Results indicate that a small number of very high profile crimes account for a significant proportion of reporting in this area and often, particularly in the tabloid press, important information regarding sentencing rationale is sidelined in favour of moral condemnation and criticism of the judiciary. Polling data indicate that public attitudes are highly critical of sentencing but also confused about the meaning of tariffs. The article concludes by discussing what can be done to promote a more informed public debate over penal policy in this area
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