10,408 research outputs found
Construction of weakly CUD sequences for MCMC sampling
In Markov chain Monte Carlo (MCMC) sampling considerable thought goes into
constructing random transitions. But those transitions are almost always driven
by a simulated IID sequence. Recently it has been shown that replacing an IID
sequence by a weakly completely uniformly distributed (WCUD) sequence leads to
consistent estimation in finite state spaces. Unfortunately, few WCUD sequences
are known. This paper gives general methods for proving that a sequence is
WCUD, shows that some specific sequences are WCUD, and shows that certain
operations on WCUD sequences yield new WCUD sequences. A numerical example on a
42 dimensional continuous Gibbs sampler found that some WCUD inputs sequences
produced variance reductions ranging from tens to hundreds for posterior means
of the parameters, compared to IID inputs.Comment: Published in at http://dx.doi.org/10.1214/07-EJS162 the Electronic
Journal of Statistics (http://www.i-journals.org/ejs/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Systemic inflammation: Cancer's long-distance reach to maximize metastasis
While major improvements have been made in targeting primary tumor growth, metastasis and combating cancer spread remain an enigma. We recently identified a systemic inflammatory cascade involving IL17-producing γδ T cells and neutrophils that advance breast cancer metastasis. These data provide insights into how immune cells promote cancer spread
Exploring strong-field deviations from general relativity via gravitational waves
Two new observational windows have been opened to strong gravitational
physics: gravitational waves, and very long baseline interferometry. This
suggests observational searches for new phenomena in this regime, and in
particular for those necessary to make black hole evolution consistent with
quantum mechanics. We describe possible features of "compact quantum objects"
that replace classical black holes in a consistent quantum theory, and
approaches to observational tests for these using gravitational waves. This is
an example of a more general problem of finding consistent descriptions of
deviations from general relativity, which can be tested via gravitational wave
detection. Simple models for compact modifications to classical black holes are
described via an effective stress tensor, possibly with an effective equation
of state. A general discussion is given of possible observational signatures,
and of their dependence on properties of the colliding objects. The possibility
that departures from classical behavior are restricted to the near-horizon
regime raises the question of whether these will be obscured in gravitational
wave signals, due to their mutual interaction in a binary coalescence being
deep in the mutual gravitational well. Numerical simulation with such simple
models will be useful to clarify the sensitivity of gravitational wave
observation to such highly compact departures from classical black holes.Comment: 20 pages, 9 figures. v2: references and CERN preprint number adde
Revving up dendritic cells while braking PD-L1 to jump-start the cancer-immunity cycle motor
Although it is successful for some, most melanoma patients are refractory to T cell checkpoint inhibition. In this issue of Immunity, Merad and colleagues (2016) describe a dendritic-cell-based strategy to heighten the efficacy of therapeutic anti-PD-L1 and BRAF inhibitors in mouse melanoma models
Volatility, Money Market Rates, and the Transmission of Monetary Policy
We explore the effect of volatility in the federal funds market on the expectations hypothesis in money markets. We find that lower volatility in the bank funding markets market, all else equal, leads to a lower term premium and thus longer-term rates for a given setting of the overnight rate. The results appear to hold for the US as well as the Euro Area and the UK. The results have implications for the design of operational frameworks for the implementation of monetary policy and for the interpretation of the changes in the Libor-OIS spread during the financial crisisMonetary transmission mechanism, expectations hypothesis, term premium
Measures of metacognition on signal-detection theoretic models
Analysing metacognition, specifically knowledge of accuracy of internal perceptual,
memorial or other knowledge states, is vital for many strands of psychology, including
determining the accuracy of feelings of knowing, and discriminating conscious from
unconscious cognition. Quantifying metacognitive sensitivity is however more challenging
than quantifying basic stimulus sensitivity. Under popular signal detection theory (SDT)
models for stimulus classification tasks, approaches based on type II receiver-operator
characteristic (ROC) curves or type II d-prime risk confounding metacognition with
response biases in either the type I (classification) or type II (metacognitive) tasks. A new
approach introduces meta-dâ˛: the type I d-prime that would have led to the observed type
II data had the subject used all the type I information. Here we (i) further establish the
inconsistency of the type II d-prime and ROC approaches with new explicit analyses of
the standard SDT model, and (ii) analyse, for the first time, the behaviour of meta-dâ˛
under non-trivial scenarios, such as when metacognitive judgments utilize enhanced or
degraded versions of the type I evidence. Analytically, meta-dⲠvalues typically reflect the
underlying model well, and are stable under changes in decision criteria; however, in
relatively extreme cases meta-dⲠcan become unstable. We explore bias and variance of
in-sample measurements of meta-dⲠand supply MATLAB code for estimation in general
cases. Our results support meta-dⲠas a useful measure of metacognition, and provide
rigorous methodology for its application. Our recommendations are useful for any
researchers interested in assessing metacognitive accuracy
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