Nonparametric inference for competing risks current status data with continuous, discrete or grouped observation times

New methods and theory have recently been developed to nonparametrically estimate cumulative incidence functions for competing risks survival data subject to current status censoring. In particular, the limiting distribution of the nonparametric maximum likelihood estimator and a simplified "naive estimator" have been established under certain smoothness conditions. In this paper, we establish the large-sample behavior of these estimators in two additional models, namely when the observation time distribution has discrete support and when the observation times are grouped. These asymptotic results are applied to the construction of confidence intervals in the three different models. The methods are illustrated on two data sets regarding the cumulative incidence of (i) different types of menopause from a cross-sectional sample of women in the United States and (ii) subtype-specific HIV infection from a sero-prevalence study in injecting drug users in Thailand.Comment: 16 pages, 3 figure

A Hybrid N-body--Coagulation Code for Planet Formation

We describe a hybrid algorithm to calculate the formation of planets from an initial ensemble of planetesimals. The algorithm uses a coagulation code to treat the growth of planetesimals into oligarchs and explicit N-body calculations to follow the evolution of oligarchs into planets. To validate the N-body portion of the algorithm, we use a battery of tests in planetary dynamics. Several complete calculations of terrestrial planet formation with the hybrid code yield good agreement with previously published calculations. These results demonstrate that the hybrid code provides an accurate treatment of the evolution of planetesimals into planets.Comment: Astronomical Journal, accepted; 33 pages + 11 figure

The upper critical field of filamentary Nb3Sn conductors

We have examined the upper critical field of a large and representative set of present multi-filamentary Nb3Sn wires and one bulk sample over a temperature range from 1.4 K up to the zero field critical temperature. Since all present wires use a solid-state diffusion reaction to form the A15 layers, inhomogeneities with respect to Sn content are inevitable, in contrast to some previously studied homogeneous samples. Our study emphasizes the effects that these inevitable inhomogeneities have on the field-temperature phase boundary. The property inhomogeneities are extracted from field-dependent resistive transitions which we find broaden with increasing inhomogeneity. The upper 90-99 % of the transitions clearly separates alloyed and binary wires but a pure, Cu-free binary bulk sample also exhibits a zero temperature critical field that is comparable to the ternary wires. The highest mu0Hc2 detected in the ternary wires are remarkably constant: The highest zero temperature upper critical fields and zero field critical temperatures fall within 29.5 +/- 0.3 T and 17.8 +/- 0.3 K respectively, independent of the wire layout. The complete field-temperature phase boundary can be described very well with the relatively simple Maki-DeGennes model using a two parameter fit, independent of composition, strain state, sample layout or applied critical state criterion.Comment: Accepted Journal of Applied Physics Few changes to shorten document, replaced eq. 7-

Risk factors associated with Rift Valley fever epidemics in South Africa in 2008-11.

Rift Valley fever (RVF) is a zoonotic and vector-borne disease, mainly present in Africa, which represents a threat to human health, animal health and production. South Africa has experienced three major RVF epidemics (1950-51, 1973-75 and 2008-11). Due to data scarcity, no previous study has quantified risk factors associated with RVF epidemics in animals in South Africa. Using the 2008-11 epidemic datasets, a retrospective longitudinal study was conducted to identify and quantify spatial and temporal environmental factors associated with RVF incidence. Cox regressions with a Besag model to account for the spatial effects were fitted to the data. Coefficients were estimated by Bayesian inference using integrated nested Laplace approximation. An increase in vegetation density was the most important risk factor until 2010. In 2010, increased temperature was the major risk factor. In 2011, after the large 2010 epidemic wave, these associations were reversed, potentially confounded by immunity in animals, probably resulting from earlier infection and vaccination. Both vegetation density and temperature should be considered together in the development of risk management strategies. However, the crucial need for improved access to data on population at risk, animal movements and vaccine use is highlighted to improve model predictions

The effect of interleukin-10 and transforming growth factor beta-1 on HLA-DR expression in colonic epithelial cells.

The aim of this study was to assess whether interleukin-10 (IL-10) and/or transforming growth factor beta-1 (TGFbeta1) downregulate HLA-DR expression using the HT29 cell line as a model of colonic epithelial cells. HLA-DR expression was induced in HT29 cells with gamma-interferon. The effects of IL-10 alone, TGFbeta1 alone, and IL-10 and TGFbeta1 in combination were studied. HLA-DR expression was assessed using flow cytometric analysis. Gamma-interferon induced HLA-DR expression in a dose-dependent fashion. In the absence of gamma-interferon, neither IL-10 nor TGFbeta1 induced HLA-DR expression. In isolation, neither IL-10 nor TGFbeta1 downregulated HLA-DR expression. When IL-10 and TGFbeta1 were added in combination, small (6-30%) statistically significant reductions in HLA-DR expression were seen. The biological significance is unclear

Joint Bayesian component separation and CMB power spectrum estimation

We describe and implement an exact, flexible, and computationally efficient algorithm for joint component separation and CMB power spectrum estimation, building on a Gibbs sampling framework. Two essential new features are 1) conditional sampling of foreground spectral parameters, and 2) joint sampling of all amplitude-type degrees of freedom (e.g., CMB, foreground pixel amplitudes, and global template amplitudes) given spectral parameters. Given a parametric model of the foreground signals, we estimate efficiently and accurately the exact joint foreground-CMB posterior distribution, and therefore all marginal distributions such as the CMB power spectrum or foreground spectral index posteriors. The main limitation of the current implementation is the requirement of identical beam responses at all frequencies, which restricts the analysis to the lowest resolution of a given experiment. We outline a future generalization to multi-resolution observations. To verify the method, we analyse simple models and compare the results to analytical predictions. We then analyze a realistic simulation with properties similar to the 3-yr WMAP data, downgraded to a common resolution of 3 degree FWHM. The results from the actual 3-yr WMAP temperature analysis are presented in a companion Letter.Comment: 23 pages, 16 figures; version accepted for publication in ApJ -- only minor changes, all clarifications. More information about the WMAP3 analysis available at http://www.astro.uio.no/~hke under the Research ta

Towards real-time classification of astronomical transients

Exploration of time domain is now a vibrant area of research in astronomy, driven by the advent of digital synoptic sky surveys. While panoramic surveys can detect variable or transient events, typically some follow-up observations are needed; for short-lived phenomena, a rapid response is essential. Ability to automatically classify and prioritize transient events for follow-up studies becomes critical as the data rates increase. We have been developing such methods using the data streams from the Palomar-Quest survey, the Catalina Sky Survey and others, using the VOEventNet framework. The goal is to automatically classify transient events, using the new measurements, combined with archival data (previous and multi-wavelength measurements), and contextual information (e.g., Galactic or ecliptic latitude, presence of a possible host galaxy nearby, etc.); and to iterate them dynamically as the follow-up data come in (e.g., light curves or colors). We have been investigating Bayesian methodologies for classification, as well as discriminated follow-up to optimize the use of available resources, including Naive Bayesian approach, and the non-parametric Gaussian process regression. We will also be deploying variants of the traditional machine learning techniques such as Neural Nets and Support Vector Machines on datasets of reliably classified transients as they build up