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At least 109 records · Page 6

Missing-Data Nonparametric Coherency Estimation

Chave recently proposed an estimator for multitaper spectral density where the time series contains missing values. In this article we generalize this technique to a multitaper estimator of coherence and phase and show that one can also obtain bootstrapped confidence intervals. Additionally, we give two examples. The first is a toy example in which the true coherence is known. In the second example we show that the multitaper missing-data coherence estimator computed on real data with a single gap comprising 11% of the data outperforms the Daniell-smoothed coherence estimator where there are no gaps. The case where the two time series have different missing indices is also discussed.

42 ENGINEERING↗

Developing a nonparametric functional calibration framework for physics-based models

Due to the cost, complexity, or difficulty in solely carrying out experiments in the effort to better understand physical phenomenon, researchers and engineers often work towards the development of computer models to represent the systems under analysis. The importance of these models in accurately representing the systems that they are designed to emulate has become a focus in numerous fields, including medicine, energy, defense, and manufacturing.

97 MATHEMATICS AND COMPUTING↗

Modeling Explosive Dispersal of Radiological Material: A Nonparametric Analysis

The National Atmospheric Release Advisory Center (NARAC) is a Department of Energy (DOE) asset that provides guidance on the potential effects of atmospherically released hazards based on dispersion simulation results. Numerical simulation results are compared to well-characterized experimental measurements whenever possible to validate and refine the model predictions. In 2012, such measurements were obtained by Defence Research and Development Canada (DRDC) and collaborating organizations for the case of explosively released 140 La – a radioactive isotope with a half-life of 1.6781 days.

42 ENGINEERING↗

Nonparametric algorithms for the search of signals

Two algorithms for the search of signals in noise are constructed. Two independent measurable properties of a discreet time-dependent stochastic process F are described. The functions A sub K and B sub K fully satisfy conditions for the application of a test based on Spearman's rank correlation coefficient. A statistic to which the one-sided signal test can be applied is constructed under sufficiently natural assumptions about the noise process. The constructed statistics are simplified. Processing results from calculations of statistics constructed for concrete processes are presented.

Myshenkova, T. S.↗

A nonparametric clustering technique which estimates the number of clusters

In applications of cluster analysis, one usually needs to determine the number of clusters, K, and the assignment of observations to each cluster. A clustering technique based on recursive application of a multivariate test of bimodality which automatically estimates both K and the cluster assignments is presented.

Ramey, D. B.↗

Nonparametric solution of the Euler equations for steady flow

A theory is presented for formulating well-posed boundary value problems for the Euler equations for steady rotational flow. It is shown that the Euler equations of motion are equivalent to a variational principle, which is used to define a finite difference scheme for numerically solving the Euler equations. The principle is extended to MHD problems in terms of a potential energy of a perfectly conducting plasma having a minimum number of stable configurations. The flow around a cylinder is considered, noting that time-independent solutions of the Euler equations can be used to provide limits to solutions of the Navier-Stokes equations. A sample is worked out in terms of the motion of vortices inside a circle.

Garabedian, P. R.↗

Nonparametric statistical modeling of binary star separations

We develop a comprehensive statistical model for the distribution of observed separations in binary star systems, in terms of distributions of orbital elements, projection effects, and distances to systems. We use this model to derive several diagnostics for estimating the completeness of imaging searches for stellar companions, and the underlying stellar multiplicities. In application to recent imaging searches for low-luminosity companions to nearby M dwarf stars, and for companions to young stars in nearby star-forming regions, our analyses reveal substantial uncertainty in estimates of stellar multiplicity. For binary stars with late-type dwarf companions, semimajor axes appear to be distributed approximately as a(exp -1) for values ranging from about one to several thousand astronomical units. About one-quarter of the companions to field F and G dwarf stars have semimajor axes less than 1 AU, and about 15% lie beyond 1000 AU. The geometric efficiency (fraction of companions imaged onto the detector) of imaging searches is nearly independent of distances to program stars and orbital eccentricities, and varies only slowly with detector spatial limitations.

Heacox, William D.↗