On the Sample Information About Parameter and Prediction

The Bayesian measure of sample information about the parameter, known as Lindley's measure, is widely used in various problems such as developing prior distributions, models for the likelihood functions and optimal designs. The predictive information is defined similarly and used for model selection and optimal designs, though to a lesser extent. The parameter and predictive information measures are proper utility functions and have been also used in combination. Yet the relationship between the two measures and the effects of conditional dependence between the observable quantities on the Bayesian information measures remain unexplored. We address both issues. The relationship between the two information measures is explored through the information provided by the sample about the parameter and prediction jointly. The role of dependence is explored along with the interplay between the information measures, prior and sampling design. For the conditionally independent sequence of observable quantities, decompositions of the joint information characterize Lindley's measure as the sample information about the parameter and prediction jointly and the predictive information as part of it. For the conditionally dependent case, the joint information about parameter and prediction exceeds Lindley's measure by an amount due to the dependence. More specific results are shown for the normal linear models and a broad subfamily of the exponential family. Conditionally independent samples provide relatively little information for prediction, and the gap between the parameter and predictive information measures grows rapidly with the sample size.Comment: Published in at http://dx.doi.org/10.1214/10-STS329 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Local Influence in Bayesian Elliptically Contoured-Ordinal Model for Mixed Data

This paper develops a new class of joint modeling of mixed correlated ordinal and continuous responses with elliptically contoured errors. This joint model includes the latent variable approach of using an elliptically contoured distribution for mixed ordinal and continuous responses. A Markov Chain Monte Carlo sampling algorithm is described for estimating the posterior distribution of the parameters. For sensitivity analysis to investigate the perturbation from associate responses, it is demonstrated how one can use some elements of covariance structure. Influence of small perturbation of these elements on the posterior normal curvature is also studied. To illustrate the application of such modeling the data (medical) is analyzed

A Multivariate Variable Model with Possibility of Missing Data on a Stochastic Process

A joint model for multivariate responses with potentially non-random missing values on a stochastic process is proposed. A full likelihood-based approach that allows yielding maximum likelihood estimates of the model parameters is used. Sensitivity of the results to the assumptions is also investigated. A common way to investigate whether perturbations of model components influence key results of the analysis is to compare the results derived from the original and perturbed models using a general index of sensitivity (ISNI). The approach is illustrated by analyzing a finance data set

A Multivariate Latent Variable Model for Mixed – Data from Continuous and Ordinal Responses with Possibility of Missing Responses

A joint model for multivariate mixed ordinal and continuous outcomes with potentially non-random missing values in both types of responses is proposed. A full likelihood-based approach is used to obtain maximum likelihood estimates of the model parameters. Some modified Pearson residuals are also introduced where the correlation between responses are taken into account. The joint modelling of responses with the possibility of missing values requires caution since the interpretation of the fitted model highly depends on the missing mechanism assumptions that are unexaminable in a fundamental sense. A common way to investigate the influence of perturbations of model components on the key results of the analysis is to compare the results derived from the original and perturbed models using an influence maximal normal curvatures. For This, influence of a small perturbation of elements of the covariance structure of the model on maximal normal curvature is also studied. To illustrate the utility of the proposed model, a large data set excerpted from the British Household Panel Survey (BHPS) is analyzed. For these data, the simultaneous effects of some covariates on life satisfaction, income and the amount of money spent on leisure activities per month as three mixed correlated responses are explored

Improving the recovery of monthly regional water storage using one year simulated observations of two pairs of GRACE-type satellite gravimetry constellation

Increasing the spatial sampling isotropy is a major issue in designing future missions dedicated to continue the task of the Gravity Recovery And Climate Experiment (GRACE) mission. From various possible future satellite gravimetry scenarios, the two-pair multi-orbit satellite configuration (Bender-type in the sequence), consisting of a coupled semi-polar pair (the same as GRACE) and an inclined pair of satellites seems to be an optimal mission choice. This contribution examines the performance of a Bender-type scenario at altitudes of 335 km and 352 km and inclinations of 89° and 63°, respectively, for improving the regional recovery of hydrological signals. To this end, we created one full year of simulated observations of the GRACE and Bender-type configurations. Our investigations include: 1) evaluating the feasible spatial resolution for the recovery of terrestrial water storage (TWS) changes in the presence of realistic instrumental noise and errors in the background models; 2) assessing the influence of aliasing errors in the TWS recovery and its separation from instrumental noise and introduced hydrological signals; and 3) analyzing the regional quality of the gravity-derived TWS results by assessing water storage changes over the 33 world major river basins. From our simulations, the Bender-derived spectral error curves indicate that, in spite of the instrumental noise, aliasing errors still contaminate the gravity fields above geopotential spherical harmonic coefficient (SHC) degree and order (d/o) 80 till 100. Regarding to the TWS recovery, we found notable improvements for the Bender-type configuration results in medium and small-scale basins, such as the Brahmaputra, Euphrates, Ganges, Indus, Mekong basins in Asia and the Yellow and Orange basins in South Africa. These results were achieved without applying post-processing, which was unachievable using simulations of one pair of GRACE-like configuration. Comparing the magnitudes of errors in the Bender-derived solutions with those of GRACE indicate that the accuracy derived from the Bender-type fields is about two times better than that of GRACE, specifically at medium spatial resolutions of 250 km (SHC d/o 80). We truncated the TWS recovery up to SHC d/o 80 in the spectral domain, whereas all comparisons are demonstrated in the spatial domain after a truncation of the solutions and WGHM field at d/o 60, since beyond this range; a relatively strong instrumental and aliasing errors contaminate the solutions. Our numerical results indicate that the spatial resolution of the Bender-type TWS recovery can be even higher for the basins with strong temporal water storage variations such as the Amazon basin. Short wavelength mass variations in basins with relatively weaker temporal TWS magnitude, such as the Murray basin, might still need the application of a filter with small averaging kernel

Antimicrobial activity of the ethanolic extract of Bryonopsis laciniosa leaf, stem, fruit and seed

Antimicrobial activity of ethanolic extract of the leaf, stem, seed and fruit of an Indian medicinal plant, Bryonopsis laciniosa, used traditionally as potent medication in healing several ailments such as adenopathy, ague, asthma, bronchitis, cholera, colic, consumption, convulsion, cough, fertility and phthisis, was tested against different pathogenic microorganisms by agar well diffusion method. Leaf and stem extracts of B. Laciniosa exhibited antimicrobial activity against different Gram positive and Gram negative bacteria. The extents of the growth inhibition of bacteria were measured for each extract and Staphylococcus aureus, Micrococcus luteus and Bacillus cerues exhibited significant growth inhibition zone. Minimum inhibitory concentrations (MIC) exhibited by stem extract against the tested organisms ranged between 0.156 and 5 mg/ml; and for leaf extracts it varied between 0.625 and 10 mg/ml. Antimicrobial activities of the crude plant extracts were comparable to those of the standard antibiotics. This study concluded that B. Laciniosa used as a traditional medicinal plant has antimicrobial activity against pathogenic microorganisms

The Economic Impact of Lower Extremity Amputations in Diabetics. a Retrospective Study From a Tertiary Care Hospital of Faisalabad, Pakistan

Background: Among the various complications of diabetes, lower-extremity amputation due to diabetic foot is a common problem. In Pakistan, 6-7% of patients with diabetes suffer from diabetic foot ulceration. Objectives: Our primary objective was to explore the frequency of diabetic foot amputations, and the secondary objective was to calculate the economic burden of these preventable surgeries on the health budget of the provincial government. Materials & Methods: It was a retrospective cross-sectional observational study conducted after obtaining approval from the Ethical Review Committee of Allied hospital, Faisalabad Medical University. The data of diabetic foot patients who underwent amputations between July 2017 and December 2017 were retrieved from three Surgical Units (I, II & III), using a purposive sampling technique. All amputations carried out for reasons other than diabetic foot were excluded. The direct medical cost of one diabetic foot amputation was calculated via a local survey of the various private hospitals of Faisalabad. The indirect costs in terms of loss of productivity and disability costs, transport costs, rehabilitation costs were not included in this study. The data were evaluated by using SPSS Version 23. Results: A total of 85 patients were included in our study. The male to female ratio was 2.7 to 1. The mean direct treatment cost for minor amputation was PKR 46926.00 ± 11730.90 ($382.35 ± 95.58), and the mean direct treatment cost for major amputation was PKR 53720.00 ± 12401.24 ($437.71 ± 101.40). Out of 85 amputations, 63 (74%) were major amputations, and the remaining 22 (26%) were minor amputations. The total cost for 63 major amputations was PKR 3,384,360 ($27568.91) and for 22 minor amputation was PKR 1,032,372 ($8409.67). The net cost came out to be PKR 4,416,732 ($35978.59) for all the 85 cases being reported in a tertiary care hospital of Faisalabad for six months. Conclusion: Diabetic foot, a preventable complication of long-term diabetes mellitus, has an economic burden on the hospital budget, which, if adequately addressed via primary prevention programme, can yield not just economical but medical benefits as well

Comparisons of atmospheric mass variations derived from ECMWF reanalysis and operational fields, over 2003 to 2011

There are two spurious jumps in the atmospheric part of the Gravity Recovery and Climate Experiment-Atmosphere and Ocean De-aliasing level 1B (GRACE-AOD1B) products, which occurred in January-February of the years 2006 and 2010, as a result of the vertical level and horizontal resolution changes in the ECMWFop (European Centre for Medium-Range Weather Forecasts operational analysis). These jumps cause a systematic error in the estimation of mass changes from GRACE time-variable level 2 products, since GRACE-AOD1B mass variations are removed during the computation of GRACE level 2. In this short note, the potential impact of using an improved set of 6-hourly atmospheric de-aliasing products on the computations of linear trends as well as the amplitude of annual and semi-annual mass changes from GRACE is assessed. These improvements result from 1) employing a modified 3D integration approach (ITG3D), and 2) using long-term consistent atmospheric fields from the ECMWF reanalysis (ERA-Interim). The monthly averages of the new ITG3D-ERA-Interim de-aliasing products are then compared to the atmospheric part of GRACE-AOD1B, covering January 2003 to December 2010. These comparisons include the 33 world largest river basins along with Greenland and Antarctica ice sheets. The results indicate a considerable difference in total atmospheric mass derived from the two products over some of the mentioned regions. We suggest that future GRACE studies consider these through updating uncertainty budgets or by applying corrections to estimated trends and amplitudes/phases

Performance Characterization of Image Feature Detectors in Relation to the Scene Content Utilizing a Large Image Database

Selecting the most suitable local invariant feature detector for a particular application has rendered the task of evaluating feature detectors a critical issue in vision research. Although the literature offers a variety of comparison works focusing on performance evaluation of image feature detectors under several types of image transformations, the influence of the scene content on the performance of local feature detectors has received little attention so far. This paper aims to bridge this gap with a new framework for determining the type of scenes which maximize and minimize the performance of detectors in terms of repeatability rate. The results are presented for several state-of-the-art feature detectors that have been obtained using a large image database of 20482 images under JPEG compression, uniform light and blur changes with 539 different scenes captured from real-world scenarios. These results provide new insights into the behavior of feature detectors