53,229 research outputs found
Hierarchical Bayesian Modeling of Hitting Performance in Baseball
We have developed a sophisticated statistical model for predicting the
hitting performance of Major League baseball players. The Bayesian paradigm
provides a principled method for balancing past performance with crucial
covariates, such as player age and position. We share information across time
and across players by using mixture distributions to control shrinkage for
improved accuracy. We compare the performance of our model to current
sabermetric methods on a held-out season (2006), and discuss both successes and
limitations
A solvable non-conservative model of Self-Organized Criticality
We present the first solvable non-conservative sandpile-like critical model
of Self-Organized Criticality (SOC), and thereby substantiate the suggestion by
Vespignani and Zapperi [A. Vespignani and S. Zapperi, Phys. Rev. E 57, 6345
(1998)] that a lack of conservation in the microscopic dynamics of an SOC-model
can be compensated by introducing an external drive and thereby re-establishing
criticality. The model shown is critical for all values of the conservation
parameter. The analytical derivation follows the lines of Broeker and
Grassberger [H.-M. Broeker and P. Grassberger, Phys. Rev. E 56, 3944 (1997)]
and is supported by numerical simulation. In the limit of vanishing
conservation the Random Neighbor Forest Fire Model (R-FFM) is recovered.Comment: 4 pages in RevTeX format (2 Figures) submitted to PR
Bayesian variable selection and data integration for biological regulatory networks
A substantial focus of research in molecular biology are gene regulatory
networks: the set of transcription factors and target genes which control the
involvement of different biological processes in living cells. Previous
statistical approaches for identifying gene regulatory networks have used gene
expression data, ChIP binding data or promoter sequence data, but each of these
resources provides only partial information. We present a Bayesian hierarchical
model that integrates all three data types in a principled variable selection
framework. The gene expression data are modeled as a function of the unknown
gene regulatory network which has an informed prior distribution based upon
both ChIP binding and promoter sequence data. We also present a variable
weighting methodology for the principled balancing of multiple sources of prior
information. We apply our procedure to the discovery of gene regulatory
relationships in Saccharomyces cerevisiae (Yeast) for which we can use several
external sources of information to validate our results. Our inferred
relationships show greater biological relevance on the external validation
measures than previous data integration methods. Our model also estimates
synergistic and antagonistic interactions between transcription factors, many
of which are validated by previous studies. We also evaluate the results from
our procedure for the weighting for multiple sources of prior information.
Finally, we discuss our methodology in the context of previous approaches to
data integration and Bayesian variable selection.Comment: Published in at http://dx.doi.org/10.1214/07-AOAS130 the Annals of
Applied Statistics (http://www.imstat.org/aoas/) by the Institute of
Mathematical Statistics (http://www.imstat.org
Complex coupled-cluster approach to an ab-initio description of open quantum systems
We develop ab-initio coupled-cluster theory to describe resonant and weakly
bound states along the neutron drip line. We compute the ground states of the
helium chain 3-10He within coupled-cluster theory in singles and doubles (CCSD)
approximation. We employ a spherical Gamow-Hartree-Fock basis generated from
the low-momentum N3LO nucleon-nucleon interaction. This basis treats bound,
resonant, and continuum states on equal footing, and is therefore optimal for
the description of properties of drip line nuclei where continuum features play
an essential role. Within this formalism, we present an ab-initio calculation
of energies and decay widths of unstable nuclei starting from realistic
interactions.Comment: 4 pages, revtex
Computation of spectroscopic factors with the coupled-cluster method
We present a calculation of spectroscopic factors within coupled-cluster
theory. Our derivation of algebraic equations for the one-body overlap
functions are based on coupled-cluster equation-of-motion solutions for the
ground and excited states of the doubly magic nucleus with mass number and
the odd-mass neighbor with mass . As a proof-of-principle calculation, we
consider O and the odd neighbors O and N, and compute the
spectroscopic factor for nucleon removal from O. We employ a
renormalized low-momentum interaction of the type derived
from a chiral interaction at next-to-next-to-next-to-leading order. We study
the sensitivity of our results by variation of the momentum cutoff, and then
discuss the treatment of the center of mass.Comment: 8 pages, 6 figures, 3 table
Medium-mass nuclei from chiral nucleon-nucleon interactions
We compute the binding energies, radii, and densities for selected
medium-mass nuclei within coupled-cluster theory and employ the "bare" chiral
nucleon-nucleon interaction at order N3LO. We find rather well-converged
results in model spaces consisting of 15 oscillator shells, and the doubly
magic nuclei 40Ca, 48Ca, and the exotic 48Ni are underbound by about 1 MeV per
nucleon within the CCSD approximation. The binding-energy difference between
the mirror nuclei 48Ca and 48Ni is close to theoretical mass table evaluations.
Our computation of the one-body density matrices and the corresponding natural
orbitals and occupation numbers provides a first step to a microscopic
foundation of the nuclear shell model.Comment: 5 pages, 5 figure
Scaling function and universal amplitude combinations for self-avoiding polygons
We analyze new data for self-avoiding polygons, on the square and triangular
lattices, enumerated by both perimeter and area, providing evidence that the
scaling function is the logarithm of an Airy function. The results imply
universal amplitude combinations for all area moments and suggest that rooted
self-avoiding polygons may satisfy a -algebraic functional equation.Comment: 9 page
A classical statistical model for distributions of escape events in swept-bias Josephson junctions
We have developed a model for experiments in which the bias current applied
to a Josephson junction is slowly increased from zero until the junction
switches from its superconducting zero-voltage state, and the bias value at
which this occurs is recorded. Repetition of such measurements yields
experimentally determined probability distributions for the bias current at the
moment of escape. Our model provides an explanation for available data on the
temperature dependence of these escape peaks. When applied microwaves are
included we observe an additional peak in the escape distributions and
demonstrate that this peak matches experimental observations. The results
suggest that experimentally observed switching distributions, with and without
applied microwaves, can be understood within classical mechanics and may not
exhibit phenomena that demand an exclusively quantum mechanical interpretation.Comment: Eight pages, eight figure
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