1,501 research outputs found
Fast increased fidelity approximate Gibbs samplers for Bayesian Gaussian process regression
The use of Gaussian processes (GPs) is supported by efficient sampling
algorithms, a rich methodological literature, and strong theoretical grounding.
However, due to their prohibitive computation and storage demands, the use of
exact GPs in Bayesian models is limited to problems containing at most several
thousand observations. Sampling requires matrix operations that scale at
where is the number of unique inputs. Storage of
individual matrices scales at and can quickly overwhelm the
resources of most modern computers. To overcome these bottlenecks, we develop a
sampling algorithm using matrix approximation of the matrices
comprising the GP posterior covariance. These matrices can approximate the true
conditional covariance matrix within machine precision and allow for sampling
algorithms that scale at \mathcal{O}(n \ \mbox{log}^2 n) time and storage
demands scaling at \mathcal{O}(n \ \mbox{log} \ n). We also describe how
these algorithms can be used as building blocks to model higher dimensional
surfaces at \mathcal{O}(d \ n \ \mbox{log}^2 n), where is the dimension
of the surface under consideration, using tensor products of one-dimensional
GPs. Though various scalable processes have been proposed for approximating
Bayesian GP inference when is large, to our knowledge, none of these
methods show that the approximation's Kullback-Leibler divergence to the true
posterior can be made arbitrarily small and may be no worse than the
approximation provided by finite computer arithmetic. We describe
matrices, give an efficient Gibbs sampler using these matrices
for one-dimensional GPs, offer a proposed extension to higher dimensional
surfaces, and investigate the performance of this fast increased fidelity
approximate GP, FIFA-GP, using both simulated and real data sets
Bayesian joint modeling of chemical structure and dose response curves
Today there are approximately 85,000 chemicals regulated under the Toxic
Substances Control Act, with around 2,000 new chemicals introduced each year.
It is impossible to screen all of these chemicals for potential toxic effects
either via full organism in vivo studies or in vitro high-throughput screening
(HTS) programs. Toxicologists face the challenge of choosing which chemicals to
screen, and predicting the toxicity of as-yet-unscreened chemicals. Our goal is
to describe how variation in chemical structure relates to variation in
toxicological response to enable in silico toxicity characterization designed
to meet both of these challenges. With our Bayesian partially Supervised Sparse
and Smooth Factor Analysis (BS3FA) model, we learn a distance between chemicals
targeted to toxicity, rather than one based on molecular structure alone. Our
model also enables the prediction of chemical dose-response profiles based on
chemical structure (that is, without in vivo or in vitro testing) by taking
advantage of a large database of chemicals that have already been tested for
toxicity in HTS programs. We show superior simulation performance in distance
learning and modest to large gains in predictive ability compared to existing
methods. Results from the high-throughput screening data application elucidate
the relationship between chemical structure and a toxicity-relevant
high-throughput assay. An R package for BS3FA is available online at
https://github.com/kelrenmor/bs3fa
Bayesian Hierarchical Factor Regression Models to Infer Cause of Death From Verbal Autopsy Data
In low-resource settings where vital registration of death is not routine it
is often of critical interest to determine and study the cause of death (COD)
for individuals and the cause-specific mortality fraction (CSMF) for
populations. Post-mortem autopsies, considered the gold standard for COD
assignment, are often difficult or impossible to implement due to deaths
occurring outside the hospital, expense, and/or cultural norms. For this
reason, Verbal Autopsies (VAs) are commonly conducted, consisting of a
questionnaire administered to next of kin recording demographic information,
known medical conditions, symptoms, and other factors for the decedent. This
article proposes a novel class of hierarchical factor regression models that
avoid restrictive assumptions of standard methods, allow both the mean and
covariance to vary with COD category, and can include covariate information on
the decedent, region, or events surrounding death. Taking a Bayesian approach
to inference, this work develops an MCMC algorithm and validates the FActor
Regression for Verbal Autopsy (FARVA) model in simulation experiments. An
application of FARVA to real VA data shows improved goodness-of-fit and better
predictive performance in inferring COD and CSMF over competing methods. Code
and a user manual are made available at https://github.com/kelrenmor/farva
Estimates of Micro-, Nano-, and Picoplankton Contributions to Particle Export in the Northeast Pacific
The contributions of micro-, nano-, and picoplankton to particle export were estimated from measurements of size-fractionated particulate 234Th, organic carbon, and phytoplankton indicator pigments obtained during five cruises between 2010 and 2012 along Line P in the subarctic northeast Pacific Ocean. Sinking fluxes of particulate organic carbon (POC) and indicator pigments were calculated from 234Th–238U disequilibria and, during two cruises, measured by sediment trap at Ocean Station Papa. POC fluxes at 100 m ranged from 0.65–7.95 mmol m−2 d−1, similar in magnitude to previous results at Line P. Microplankton pigments dominate indicator pigment fluxes (averaging 69 ± 19% of total pigment flux), while nanoplankton pigments comprised the majority of pigment standing stocks (averaging 64 ± 23% of total pigment standing stock). Indicator pigment loss rates (the ratio of pigment export flux to pigment standing stock) point to preferential export of larger microplankton relative to smaller nano- and picoplankton. However, indicator pigments do not quantitatively trace particle export resulting from zooplankton grazing, which may be an important pathway for the export of small phytoplankton. These results have important implications for understanding the magnitude and mechanisms controlling the biological pump at Line P in particular, and more generally in oligotrophic gyres and high-nutrient, low-chlorophyll regions where small phytoplankton represent a major component of the autotrophic community
Elevation of 1-Hour Plasma Glucose During Oral Glucose Tolerance Testing Is Associated With Worse Pulmonary Function in Cystic Fibrosis
Cosmic-Enu: An emulator for the non-linear neutrino power spectrum
Cosmology is poised to measure the neutrino mass sum and has
identified several smaller-scale observables sensitive to neutrinos,
necessitating accurate predictions of neutrino clustering over a wide range of
length scales. The FlowsForTheMasses non-linear perturbation theory for the
massive neutrino power spectrum, , agrees with its companion
N-body simulation at the level for Mpc. Building upon
the Mira-Titan IV emulator for the cold matter, we use FlowsForTheMasses to
construct an emulator for covering a large range of
cosmological parameters and neutrino fractions ,
which corresponds to ~eV. Consistent with FlowsForTheMasses at
the level, it returns a power spectrum in milliseconds. Ranking the
neutrinos by initial momenta, we also emulate the power spectra of momentum
deciles, providing information about their perturbed distribution function.
Comparing a ~eV model to a wide range of N-body simulation methods,
we find agreement to for Mpc and to
for Mpc. We find that the enhancement factor, the ratio
of to its linear-response equivalent, is most strongly
correlated with , and also with the clustering amplitude
. Furthermore, non-linearities enhance the free-streaming-limit
scaling
beyond its linear value of 4, increasing the -sensitivity of the
small-scale neutrino density.Comment: 17 pages, 14 figures, 3 tables. Emulator code available at:
https://github.com/upadhye/Cosmic-En
Empirical Validation of a New Data Product from the Interstellar Boundary Explorer Satellite
Since 2008, the Interstellar Boundary Explorer (IBEX) satellite has been
gathering data on heliospheric energetic neutral atoms (ENAs) while being
exposed to various sources of background noise, such as cosmic rays and solar
energetic particles. The IBEX mission initially released only a qualified
triple-coincidence (qABC) data product, which was designed to provide
observations of ENAs free of background contamination. Further measurements
revealed that the qABC data was in fact susceptible to contamination, having
relatively low ENA counts and high background rates. Recently, the mission team
considered releasing a certain qualified double-coincidence (qBC) data product,
which has roughly twice the detection rate of the qABC data product. This paper
presents a simulation-based validation of the new qBC data product against the
already-released qABC data product. The results show that the qBCs can
plausibly be said to share the same signal rate as the qABCs up to an average
absolute deviation of 3.6%. Visual diagnostics at an orbit, map, and full
mission level provide additional confirmation of signal rate coherence across
data products. These approaches are generalizable to other scenarios in which
one wishes to test whether multiple observations could plausibly be generated
by some underlying shared signal
Assimilating Remote Sensing Observations of Leaf Area Index and Soil Moisture for Wheat Yield Estimates: An Observing System Simulation Experiment
Observing system simulation experiments were used to investigate ensemble Bayesian state updating data assimilation of observations of leaf area index (LAI) and soil moisture (theta) for the purpose of improving single-season wheat yield estimates with the Decision Support System for Agrotechnology Transfer (DSSAT) CropSim-Ceres model. Assimilation was conducted in an energy-limited environment and a water-limited environment. Modeling uncertainty was prescribed to weather inputs, soil parameters and initial conditions, and cultivar parameters and through perturbations to model state transition equations. The ensemble Kalman filter and the sequential importance resampling filter were tested for the ability to attenuate effects of these types of uncertainty on yield estimates. LAI and theta observations were synthesized according to characteristics of existing remote sensing data, and effects of observation error were tested. Results indicate that the potential for assimilation to improve end-of-season yield estimates is low. Limitations are due to a lack of root zone soil moisture information, error in LAI observations, and a lack of correlation between leaf and grain growth
Spectropolarimetric Evidence for Radiatively Inefficient Accretion in an Optically Dull Active Galaxy
We present Subaru/FOCAS spectropolarimetry of two active galaxies in the
Cosmic Evolution Survey. These objects were selected to be optically dull, with
the bright X-ray emission of an AGN but missing optical emission lines in our
previous spectroscopy. Our new observations show that one target has very weak
emission lines consistent with an optically dull AGN, while the other object
has strong emission lines typical of a host-diluted Type 2 Seyfert galaxy. In
neither source do we observe polarized emission lines, with 3-sigma upper
limits of P_BLR < 2%. This means that the missing broad emission lines (and
weaker narrow emission lines) are not due to simple anisotropic obscuration,
e.g., by the canonical AGN torus. The weak-lined optically dull AGN exhibits a
blue polarized continuum with P = 0.78 +/- 0.07% at 4400 A < lambda_rest < 7200
A (P = 1.37 +/- 0.16% at 4400 A < lambda_rest < 5050 A). The wavelength
dependence of this polarized flux is similar to that of an unobscured AGN
continuum and represents the intrinsic AGN emission, either as synchrotron
emission or the outer part of an accretion disk reflected by a clumpy dust
scatterer. Because this intrinsic AGN emission lacks emission lines, this
source is likely to have a radiatively inefficient accretion flow.Comment: Accepted to ApJ. 6 pages, 2 figure
- …