Metropolized Randomized Maximum Likelihood for sampling from multimodal distributions

This article describes a method for using optimization to derive efficient independent transition functions for Markov chain Monte Carlo simulations. Our interest is in sampling from a posterior density $\pi(x)$ for problems in which the dimension of the model space is large, $\pi(x)$ is multimodal with regions of low probability separating the modes, and evaluation of the likelihood is expensive. We restrict our attention to the special case for which the target density is the product of a multivariate Gaussian prior and a likelihood function for which the errors in observations are additive and Gaussian

Randomised maximum likelihood based posterior sampling

Minimization of a stochastic cost function is commonly used for approximate sampling in high-dimensional Bayesian inverse problems with Gaussian prior distributions and multimodal posterior distributions. The density of the samples generated by minimization is not the desired target density, unless the observation operator is linear, but the distribution of samples is useful as a proposal density for importance sampling or for Markov chain Monte Carlo methods. In this paper, we focus on applications to sampling from multimodal posterior distributions in high dimensions. We first show that sampling from multimodal distributions is improved by computing all critical points instead of only minimizers of the objective function. For applications to high-dimensional geoscience problems, we demonstrate an efficient approximate weighting that uses a low-rank Gauss-Newton approximation of the determinant of the Jacobian. The method is applied to two toy problems with known posterior distributions and a Darcy flow problem with multiple modes in the posterior

Cows’ milk exclusion diet during infancy: is there a long term effect on children's eating behaviour and food preferences?

Background: Dietary restriction during infancy may influence later eating behaviour. The aim of this study was to determine if consuming a cows’ milk exclusion (CME) diet during infancy affects eating habits in later childhood, once cows’ milk has been reintroduced into the diet. Methods: Children were recruited from two large birth cohort studies in the UK. A small number of participants were recruited from allergy clinic. Two groups were recruited: an experimental group of children who had consumed a CME diet during infancy and a control group, who had consumed an unrestricted diet during infancy. Parents and children completed questionnaires regarding eating behaviour and food preferences. Results: 101 children of mean age 11.5 years were recruited (28 CME and 73 control). The CME group scored significantly higher on “slowness of eating” and on the combined “avoidant eating behaviour” construct (p < 0.01). The number of foods avoided and symptoms were associated with higher levels of avoidant eating behaviour (p < 0.05). The CME group rated liking for several dairy foods (butter, cream, chocolate, full fat milk and ice cream) significantly lower than the control group (p < 0.05), although there were no significant differences seen for any other category of food. Conclusion: This study demonstrated that consuming a CME diet during infancy has persistent and long-term effects on eating habits and food preferences. To reduce future negative eating behaviours, children’s exclusion diets need to be as varied as possible and reintroduction of cows’ milk products closely monitored

Notorious places: image, reputation, stigma: the role of newspapers in area reputations for social housing estates

This paper reviews work in several disciplines to distinguish between image, reputation and stigma. It also shows that there has been little research on the process by which area reputations are established and sustained through transmission processes. This paper reports on research into the portrayal of two social housing estates in the printed media over an extended period of time (14 years). It was found that negative and mixed coverage of the estates dominated, with the amount of positive coverage being very small. By examining the way in which dominant themes were used by newspapers in respect of each estate, questions are raised about the mode of operation of the press and the communities' collective right to challenge this. By identifying the way regeneration stories are covered and the nature of the content of positive stories, lessons are drawn for programmes of area transformation. The need for social regeneration activities is identified as an important ingredient for changing deprived-area reputations

Measuring The Evolutionary Rate Of Cooling Of ZZ Ceti

We have finally measured the evolutionary rate of cooling of the pulsating hydrogen atmosphere (DA) white dwarf ZZ Ceti (Ross 548), as reflected by the drift rate of the 213.13260694 s period. Using 41 yr of time-series photometry from 1970 November to 2012 January, we determine the rate of change of this period with time to be dP/dt = (5.2 +/- 1.4) x 10(-15) s s(-1) employing the O - C method and (5.45 +/- 0.79) x 10(-15) s s(-1) using a direct nonlinear least squares fit to the entire lightcurve. We adopt the dP/dt obtained from the nonlinear least squares program as our final determination, but augment the corresponding uncertainty to a more realistic value, ultimately arriving at the measurement of dP/dt = (5.5 +/- 1.0) x 10(-15) s s(-1). After correcting for proper motion, the evolutionary rate of cooling of ZZ Ceti is computed to be (3.3 +/- 1.1) x 10(-15) s s(-1). This value is consistent within uncertainties with the measurement of (4.19 +/- 0.73) x 10(-15) s s(-1) for another similar pulsating DA white dwarf, G 117-B15A. Measuring the cooling rate of ZZ Ceti helps us refine our stellar structure and evolutionary models, as cooling depends mainly on the core composition and stellar mass. Calibrating white dwarf cooling curves with this measurement will reduce the theoretical uncertainties involved in white dwarf cosmochronometry. Should the 213.13 s period be trapped in the hydrogen envelope, then our determination of its drift rate compared to the expected evolutionary rate suggests an additional source of stellar cooling. Attributing the excess cooling to the emission of axions imposes a constraint on the mass of the hypothetical axion particle.NSF AST-1008734, AST-0909107Norman Hackerman Advanced Research Program 003658-0252-2009Astronom

Measuring The Evolutionary Rate Of Cooling Of ZZ Ceti

We have finally measured the evolutionary rate of cooling of the pulsating hydrogen atmosphere (DA) white dwarf ZZ Ceti (Ross 548), as reflected by the drift rate of the 213.13260694 s period. Using 41 yr of time-series photometry from 1970 November to 2012 January, we determine the rate of change of this period with time to be dP/dt = (5.2 +/- 1.4) x 10(-15) s s(-1) employing the O - C method and (5.45 +/- 0.79) x 10(-15) s s(-1) using a direct nonlinear least squares fit to the entire lightcurve. We adopt the dP/dt obtained from the nonlinear least squares program as our final determination, but augment the corresponding uncertainty to a more realistic value, ultimately arriving at the measurement of dP/dt = (5.5 +/- 1.0) x 10(-15) s s(-1). After correcting for proper motion, the evolutionary rate of cooling of ZZ Ceti is computed to be (3.3 +/- 1.1) x 10(-15) s s(-1). This value is consistent within uncertainties with the measurement of (4.19 +/- 0.73) x 10(-15) s s(-1) for another similar pulsating DA white dwarf, G 117-B15A. Measuring the cooling rate of ZZ Ceti helps us refine our stellar structure and evolutionary models, as cooling depends mainly on the core composition and stellar mass. Calibrating white dwarf cooling curves with this measurement will reduce the theoretical uncertainties involved in white dwarf cosmochronometry. Should the 213.13 s period be trapped in the hydrogen envelope, then our determination of its drift rate compared to the expected evolutionary rate suggests an additional source of stellar cooling. Attributing the excess cooling to the emission of axions imposes a constraint on the mass of the hypothetical axion particle.NSF AST-1008734, AST-0909107Norman Hackerman Advanced Research Program 003658-0252-2009Astronom

MAPPING OF RESERVOIR PROPERTIES AND FACIES THROUGH INTEGRATION OF STATIC AND DYNAMIC DATA

Knowledge of the distribution of permeability and porosity in a reservoir is necessary for the prediction of future oil production, estimation of the location of bypassed oil, and optimization of reservoir management. But while the volume of data that can potentially provide information on reservoir architecture and fluid distributions has increased enormously in the past decade, it is not yet possible to make use of all the available data in an integrated fashion. While it is relatively easy to generate plausible reservoir models that honor static data such as core, log, and seismic data, it is far more difficult to generate plausible reservoir models that honor dynamic data such as transient pressures, saturations, and flow rates. As a result, the uncertainty in reservoir properties is higher than it could be and reservoir management can not be optimized. The goal of this project is to develop computationally efficient automatic history matching techniques for generating geologically plausible reservoir models which honor both static and dynamic data. Solution of this problem is necessary for the quantification of uncertainty in future reservoir performance predictions and for the optimization of reservoir management. Facies (defined here as regions of relatively uniform petrophysical properties) are common features of all reservoirs. Because the flow properties of the various facies can vary greatly, knowledge of the location of facies boundaries is of utmost importance for the prediction of reservoir performance and for the optimization of reservoir management. When the boundaries between facies are fairly well known, but flow properties are poorly known, the average properties for all facies can be determined using traditional techniques. Traditional history matching honors dynamic data by adjusting petrophysical properties in large areas, but in the process of adjusting the reservoir model ignores the static data and often results in implausible reservoir models. In general, boundary locations, average permeability and porosity, relative permeability curves, and local flow properties may all need to be adjusted to achieve a plausible reservoir model that honors all data. In this project, we will characterize the distribution of geologic facies as an indicator random field, making use of the tools of geostatistics as well as the tools of inverse and probability theory for data integration

Open defecation and childhood stunting in India: an ecological analysis of new data from 112 districts.

Poor sanitation remains a major public health concern linked to several important health outcomes; emerging evidence indicates a link to childhood stunting. In India over half of the population defecates in the open; the prevalence of stunting remains very high. Recently published data on levels of stunting in 112 districts of India provide an opportunity to explore the relationship between levels of open defecation and stunting within this population. We conducted an ecological regression analysis to assess the association between the prevalence of open defecation and stunting after adjustment for potential confounding factors. Data from the 2011 HUNGaMA survey was used for the outcome of interest, stunting; data from the 2011 Indian Census for the same districts was used for the exposure of interest, open defecation. After adjustment for various potential confounding factors--including socio-economic status, maternal education and calorie availability--a 10 percent increase in open defecation was associated with a 0.7 percentage point increase in both stunting and severe stunting. Differences in open defecation can statistically account for 35 to 55 percent of the average difference in stunting between districts identified as low-performing and high-performing in the HUNGaMA data. In addition, using a Monte Carlo simulation, we explored the effect on statistical power of the common practice of dichotomizing continuous height data into binary stunting indicators. Our simulation showed that dichotomization of height sacrifices statistical power, suggesting that our estimate of the association between open defecation and stunting may be a lower bound. Whilst our analysis is ecological and therefore vulnerable to residual confounding, these findings use the most recently collected large-scale data from India to add to a growing body of suggestive evidence for an effect of poor sanitation on human growth. New intervention studies, currently underway, may shed more light on this important issue