On calibrated weights in stratified sampling

In this paper, we propose a calibration estimator of population mean in stratified sampling using the known mean and variance information from multi-auxiliary variables. The problem of determining the optimum calibrated weights is formulated as a Nonlinear Programming Problem (NLPP) that is solved using the Lagrange multiplier technique. Numerical example with real data is presented to illustrate the computational details of the proposed estimator. A comparison study is also carried out using real and simulated data to evaluate the performance and the usefulness of the proposed estimator. The study reveals that the proposed estimator with multi-auxiliary information is more efficient estimator of the population mean as it provides least estimated variance and highest gain in relative efficiency (RE). References Jean Claude Deville and Carl Erik Sarndal. Calibration estimators in survey sampling. Journal of the American statistical Association, 87(418):376–382, 1992. doi:10.1080/01621459.1992.10475217. Victor M Estevao and Carl Erik Sarndal. Survey estimates by calibration on complex auxiliary information. International Statistical Review, 74(2):127–147, 2006. doi:110.1111/j.1751-5823.2006.tb00165.x Patrick J Farrell and Sarjinder Singh. Model-assisted higher-order calibration of estimators of variance. Australian and New Zealand Journal of Statistics, 47(3):375–383, 2005. doi:10.1111/j.1467-842X.2005.00402.x Wolfram Research, Inc. Mathematica, Version 11.3. Champaign, IL, 2018. Jong Min Kim, Engin A Sungur, and Tae Young Heo. Calibration approach estimators in stratified sampling. Statistics and probability letters, 77(1):99–103, 2007. doi:10.1016/j.spl.2006.05.015 Phillip S Kott. Using calibration weighting to adjust for nonresponse and coverage errors. Survey Methodology, 32(2):133, 2006. Dinesh K Rao. Mathematical programing in stratified random sampling. PhD thesis, School of Computing, Information and Mathematical Sciences, The University of the South Pacific, Fiji, February 2017. Dinesh K. Rao, Tokaua. Tekabu, and Mohammad G M Khan. New calibration estimators in stratified sampling. In Proceedings of Asia-Pacific World Congress on Computer Science and Engineering, pages 66–70. IEEE, 2016. Gurmindar K Singh, Dinesh K Rao, and Mohammed GM Khan. Calibration estimator of population mean in stratified random sampling. In Proceedings of Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE), pages 1–5. IEEE, 2014. Sarjindar Singh, Stephen Horn, and Frank Yu. Estimation of variance of general regression estimator: Higher level calibration approach. Survey Methodology, 24:41–50, 1998. Sarjinder Singh. Advanced Sampling Theory With Applications: How Michael "Selected" Amy, volume I and II. Kluwer Academic Publishers, Netherlands, 2003. Sarjinder Singh. On the calibration of design weights using a displacement function. Metrika, 75(1):85–107, 2012. doi:10.1007/s00184-010-0316-6 Sarjinder Singh, Stephen Horn, Sadeq Chowdhury, and Frank Yu. Theory and methods: Calibration of the estimators of variance. Australian and New Zealand Journal of Statistics, 41(2):199–212, 1999. doi:10.1111/1467-842X.00074 D S Tracy, S Singh, and R Arnab. Note on calibration in stratified and double sampling. Survey Methodology, 29(1):99–104, 2003. Changbao Wu and Randy R Sitter. A model-calibration approach to using complete auxiliary information from survey data. Journal of the American Statistical Association, 96(453):185–193, 2001. doi:10.1198/01621450175033305

On calibrated weights in stratified sampling

In this paper, we propose a calibration estimator of population mean in stratified sampling using the known mean and variance information from multi-auxiliary variables. The problem of determining the optimum calibrated weights is formulated as a Nonlinear Programming Problem (NLPP) that is solved using the Lagrange multiplier technique. Numerical example with real data is presented to illustrate the computational details of the proposed estimator. A comparison study is also carried out using real and simulated data to evaluate the performance and the usefulness of the proposed estimator. The study reveals that the proposed estimator with multi-auxiliary information is more efficient estimator of the population mean as it provides least estimated variance and highest gain in relative efficiency (RE). References Jean Claude Deville and Carl Erik Sarndal. Calibration estimators in survey sampling. Journal of the American statistical Association, 87(418):376–382, 1992. doi:10.1080/01621459.1992.10475217. Victor M Estevao and Carl Erik Sarndal. Survey estimates by calibration on complex auxiliary information. International Statistical Review, 74(2):127–147, 2006. doi:110.1111/j.1751-5823.2006.tb00165.x Patrick J Farrell and Sarjinder Singh. Model-assisted higher-order calibration of estimators of variance. Australian and New Zealand Journal of Statistics, 47(3):375–383, 2005. doi:10.1111/j.1467-842X.2005.00402.x Wolfram Research, Inc. Mathematica, Version 11.3. Champaign, IL, 2018. Jong Min Kim, Engin A Sungur, and Tae Young Heo. Calibration approach estimators in stratified sampling. Statistics and probability letters, 77(1):99–103, 2007. doi:10.1016/j.spl.2006.05.015 Phillip S Kott. Using calibration weighting to adjust for nonresponse and coverage errors. Survey Methodology, 32(2):133, 2006. Dinesh K Rao. Mathematical programing in stratified random sampling. PhD thesis, School of Computing, Information and Mathematical Sciences, The University of the South Pacific, Fiji, February 2017. Dinesh K. Rao, Tokaua. Tekabu, and Mohammad G M Khan. New calibration estimators in stratified sampling. In Proceedings of Asia-Pacific World Congress on Computer Science and Engineering, pages 66–70. IEEE, 2016. Gurmindar K Singh, Dinesh K Rao, and Mohammed GM Khan. Calibration estimator of population mean in stratified random sampling. In Proceedings of Asia-Pacific World Congress on Computer Science and Engineering (APWC on CSE), pages 1–5. IEEE, 2014. Sarjindar Singh, Stephen Horn, and Frank Yu. Estimation of variance of general regression estimator: Higher level calibration approach. Survey Methodology, 24:41–50, 1998. Sarjinder Singh. Advanced Sampling Theory With Applications: How Michael "Selected" Amy, volume I and II. Kluwer Academic Publishers, Netherlands, 2003. Sarjinder Singh. On the calibration of design weights using a displacement function. Metrika, 75(1):85–107, 2012. doi:10.1007/s00184-010-0316-6 Sarjinder Singh, Stephen Horn, Sadeq Chowdhury, and Frank Yu. Theory and methods: Calibration of the estimators of variance. Australian and New Zealand Journal of Statistics, 41(2):199–212, 1999. doi:10.1111/1467-842X.00074 D S Tracy, S Singh, and R Arnab. Note on calibration in stratified and double sampling. Survey Methodology, 29(1):99–104, 2003. Changbao Wu and Randy R Sitter. A model-calibration approach to using complete auxiliary information from survey data. Journal of the American Statistical Association, 96(453):185–193, 2001. doi:10.1198/01621450175033305

The Dynamics of a Classical Spinning Particle in Vaidya Space-Time

Based on the Mathisson-Papapetrou-Dixon (MPD) equations and the Vaidya metric, the motion of a spinning point particle orbiting a non-rotating star while undergoing radiation-induced gravitational collapse is studied in detail. A comprehensive analysis of the orbital dynamics is performed assuming distinct central mass functions which satisfy the weak energy condition, in order to determine a correspondence between the choice of mass function and the spinning particle's orbital response, as reflected in the gravitational waves emitted by the particle. The analysis presented here is likely most beneficial for the observation of rotating solar mass black holes or neutron stars in orbit around intermediate-sized Schwarzschild black holes undergoing radiation collapse. The possibility of detecting the effects of realistic mass accretion based on this approach is considered. While it seems unlikely to observe such effects based on present technology, they may perhaps become observable with the advent of future detectors.Comment: REVTeX file, 20 pages, 26 figure

STUDY OF HRCT CHEST FINDINGS AND SEVERITY SCORE IN COVID-19 PATIENTS AND ITS CORRELATION WITH CLINICAL AND LABORATORY PARAMETERS

Objectives: High-resolution computed tomography (HRCT) refers to a CT scan that gives a more precise cross-section image of the lungs than a regular chest CT and chest X-ray. HRCT chest uses specific technologies for better image resolution with exquisite lung details ideal for assessment. This modality can be applied in diagnosing and grading severity in coronavirus disease 2019 (COVID-19) infection. HRCT is more sensitive and accurate in diagnosing diffuse lung disease. Since HRCT can detect even small nodules in the lungs, it can detect severe abnormalities at an early stage of the infection and help to plan appropriate treatment. The aim of the study was to study HRCT chest findings in patients with COVID-19 infection and correlation with clinical and laboratory parameters.   Methods: This was a prospective and retrospective observational study done for duration of 1 year, that is, from June 2020 to May 2021 in the Department of Radio-diagnosis at Shri Sathya Sai Medical College and Research Institute, Tiruporur-Guduvancherry, Main Road, Ammapettai, Nellikuppam, Kancheepuram district on 235 COVID-19 positive patients. Results: The typical findings were ground glass opacity + reticular pattern (GGO +crazy paving) noted 50.2% moderate cases and 13.2% severe cases. The mild group (CT-SS of 1–8) consisted of 56 patients (23.83%), moderate group (CT-SS of 9–12) consisted of 143 (60.85%) patients where as severe group (CT-SS of >13) was composed of 36 (15.32%). Conclusion: HRCT chest plays an important role in early identification of the COVID-19 infection. HRCT severity score helps to the patients in guiding the treatment and monitor disease progression

Light from Cascading Partons in Relativistic Heavy-Ion Collisions

We calculate the production of high energy photons from Compton and annihilation processes as well as fragmentation off quarks in the parton cascade model. The multiple scattering of partons is seen to lead to a substantial production of high energy photons, which rises further when parton multiplication due to final state radiation is included. The photon yield is found to be proportional to the number of collisions among the cascading partons.Comment: revised version: 4 pages, 4 figures, uses REVTEX

Heterogeneous Ensemble Variable Selection To Improve Customer Prediction Using Naive Bayes Model

The analysis of customer patterns and behaviours is essential for all businesses, as the customer is the sole source of revenue. Understanding customer patterns and behavior enables businesses to enhance their business processes and customer happiness. The availability of voluminous client datasets within organizations facilitates efficient customer analysis. Yet, the inclusion of interrelated, irrelevant, as well as missing factors leads to a poor forecast of the dataset. Feature selection techniques are investigated in order to handle the problem. Objective of feature selection is to pick the pertinent variables from a complete set of associated, irrelevant, and missing variables. In general, FS is classified into 3 types: filter, wrapper, & hybrid method. The filter method is a quick one, but the variables used are ineffective. Similarly, a wrapper method is effective yet computationally inefficient. In this study, an ensemble feature selection strategy is presented and tested to circumvent the issue with these feature selections. There are two techniques to ensemble FS: one is homogenous and the other is heterogeneous. This study employs a heterogeneous ensemble feature selection method. In the suggested method, the learning dataset is applied to five distinct filter FS approaches, and the ranked attributes that result are aggregated using two distinct methods: the mean method and the min method. Relevant variables are chosen to further build the final sorted qualities using the cut off value as a guide. As the HEVS technique's filter approach simply ranks the variables, it is necessary to select the variable subset cut off value. The experimental technique is conducted from two distinct vantage points: Heterogeneous ensemble variable selection with Naive Bayes and Naive Bayes without variable selection. In the end, the outcomes that were obtained via the use of the two different approaches are compared using different factors. The experimental results demonstrate that the suggested HEVS method outperforms the usual Naive Bayes model. As relevant variables are included when modeling using NB, the computational complexity of this proposed methodology is also minimized

Effect of Liquefaction Induced Lateral Spreading on Seismic Performance of Pile Foundations

Seismically active areas are vulnerable to liquefaction, and the influence of liquefaction on pile foundations is very severe. Study of pile-supported buildings in liquefiable soils requires consideration of soil-pile interaction and evaluation of the interaction resulting from movement of soil surrounding the pile. This paper presents the results of three-dimensional finite difference analyses conducted to understand the effect of liquefiable soils on the seismic performance of piles and pile groups embedded in stratified soil deposits using the numerical tool FLAC3D. A comparative study has been conducted on the performance of pile foundations on level ground and sloping ground. The soil model consists of a non-liquefiable, slightly cemented sand layer at the top and bottom and a liquefiable Nevada sand layer in between. This stratified ground is subjected to 1940 El Centro, 2001 Bhuj (India) earthquake ground motions, and harmonic motion of 0.3g acceleration. Parametric studies have been carried out by changing the ground slope from 0° to 10° to understand the effects of sloping ground on pile group response. The results indicate that the maximum bending moments occur at boundaries between liquefiable and non-liquefiable layers, and that the bending moment increases with an increase in slope angle. The presence of a pile cap prevents horizontal ground displacements at ground level. Further, it is also observed that the displacements of pile groups under sloping ground are in excess of those on level ground due to lateral spreading. Doi: 10.28991/CEJ-SP2021-07-05 Full Text: PD

Can Gravity Distinguish Between Dirac and Majorana Neutrinos?

We show that spin-gravity interaction can distinguish between Dirac and Majorana neutrino wave packets propagating in a Lense-Thirring background. Using time-independent perturbation theory and gravitational phase to generate a perturbation Hamiltonian with spin-gravity coupling, we show that the associated matrix element for the Majorana neutrino differs significantly from its Dirac counterpart. This difference can be demonstrated through significant gravitational corrections to the neutrino oscillation length for a two-flavour system, as shown explicitly for SN1987A.Comment: 4 pages, 2 figures; minor changes of text; typo corrected; accepted in Physical Review Letter

Low NT-proBNP levels in overweight and obese patients do not rule out a diagnosis of heart failure with preserved ejection fraction

Background Heart failure with preserved ejection fraction (HFpEF) is a heterogeneous syndrome that presents clinicians with a diagnostic challenge. The use of natriuretic peptides to exclude a diagnosis of HFpEF has been proposed. We sought to compare HFpEF patients with N-terminal pro-brain natriuretic peptide (NT-proBNP) level above and below the proposed cut-off. Methods Stable patients (n = 30) with left ventricular (LV) ejection fraction ≥ 50% were eligible if they had a diagnosis of HF according to the European Society of Cardiology diagnostic criteria. Characteristics of patients with NT-proBNP below (≤125 pg/mL) and above (\u3e125 pg/mL) the diagnostic criterion were compared. Results There were 19 (66%) women with median age 54 years. Half were African American (16, 53%), and most were obese. There were no significant differences in clinical characteristics or medication use between groups. LV end-diastolic volume index was greater in high NT-proBNP patients (P = 0.03). Left atrial volume index, E/e\u27 ratio, and E/e\u27 ratio at peak exercise were not significantly different between NT-proBNP groups. Peak oxygen consumption (VO2), VO2 at ventilatory threshold, and ventilatory efficiency measures were impaired in all patients and were not significantly different between high and low NT-proBNP patients. Conclusions NT-proBNP was below the proposed diagnostic cut-off point of 125 pg/mL in half of this obese study cohort. Cardiac diastolic dysfunction and cardiorespiratory fitness were not significantly different between high and low NT-proBNP patients. These data indicate that excluding the diagnosis of HFpEF based solely on NT-proBNP levels should be discouraged