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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Statistical tests of ARIES data

Statistical tests are performed on Project ARIES preliminary baseline measurements in the Southern California triangle formed by the Jet Propulsion Laboratory, the Owens Valley Radio Observatory, and the Goldstone tracking complex during 1976-1980. In addition to conventional one-dimensional tests a two-dimensional test which allows for an arbitrary correlation between errors in individual components is formulated using the Hotelling statistic. On two out of three baselines the mean rate of change in baseline vector is statistically significant. Apparent motions on all three baselines are consistent with a pure shear with north-south compression and east-west expansion of 1 x 10 to the -7th/year. The ARIES measurements are consistent with the USGS geodolite networks in Southern California and the SAFE laser satellite ranging experiment. All three experiments are consistent with a 6 cm/year motion between the Pacific and North American Plates and a band of diffuse shear 300 km wide, except that corresponding rotation of the entire triangle is not found.

Musman, S.↗
DOE OSTI2020

Statistical Tests for Diagnosing Fission Source Convergence and Undersampling in Monte Carlo Criticality Calculations [Slides]

There is a very strong need for statistical testing to determine fission source convergence in Monte Carlo criticality calculations. Automation of such tests will greatly streamline and support the work carried out by NCS practitioners. Recent R&D work has shown that no single statistical test for convergence is sufficiently reliable, robust, and “guaranteed.” However, a combination of several standard statistical tests for the similarity of distributions, coupled with a high-fidelity estimate of the fission-matrix source is sufficiently robust, reliable, and repeatable that convergence can be “guaranteed.” During the course of the EG-AMCT studies, a number of statistical metrics and tests were proposed for diagnosing clustering and undersampling. None of these was robust and reliable enough for practical use in production codes. However, the expert group efforts came close. Some recent R&D work stemming from those past efforts has been very successful and promising. This Sub-Group will provide international input and collaboration on the development and implementation of statistical tests for convergence, with the primary goal of having the MC codes automatically detect convergence (or lack thereof). Newly proposed statistical tests to detect undersampling (after convergence) will also be reviewed.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
NASA NTRS1984

Statistical tests of additional plate boundaries from plate motion inversions

The application of the F-ratio test, a standard statistical technique, to the results of relative plate motion inversions has been investigated. The method tests whether the improvement in fit of the model to the data resulting from the addition of another plate to the model is greater than that expected purely by chance. This approach appears to be useful in determining whether additional plate boundaries are justified. Previous results have been confirmed favoring separate North American and South American plates with a boundary located beween 30 N and the equator. Using Chase's global relative motion data, it is shown that in addition to separate West African and Somalian plates, separate West Indian and Australian plates, with a best-fitting boundary between 70 E and 90 E, can be resolved. These results are generally consistent with the observation that the Indian plate's internal deformation extends somewhat westward of the Ninetyeast Ridge. The relative motion pole is similar to Minster and Jordan's and predicts the NW-SE compression observed in earthquake mechanisms near the Ninetyeast Ridge.

Stein, S.↗
DOE OSTI2024

To have value, comparisons of high-throughput phenotyping methods need statistical tests of bias and variance

The gap between genomics and phenomics is narrowing. The rate at which it is narrowing, however, is being slowed by improper statistical comparison of methods. Quantification using Pearson’s correlation coefficient ( r ) is commonly used to assess method quality, but it is an often misleading statistic for this purpose as it is unable to provide information about the relative quality of two methods. Using r can both erroneously discount methods that are inherently more precise and validate methods that are less accurate. These errors occur because of logical flaws inherent in the use of r when comparing methods, not as a problem of limited sample size or the unavoidable possibility of a type I error. A popular alternative to using r is to measure the limits of agreement (LOA). However both r and LOA fail to identify which instrument is more or less variable than the other and can lead to incorrect conclusions about method quality. An alternative approach, comparing variances of methods, requires repeated measurements of the same subject, but avoids incorrect conclusions. Variance comparison is arguably the most important component of method validation and, thus, when repeated measurements are possible, variance comparison provides considerable value to these studies. Statistical tests to compare variances presented here are well established, easy to interpret and ubiquitously available. The widespread use of r has potentially led to numerous incorrect conclusions about method quality, hampering development, and the approach described here would be useful to advance high throughput phenotyping methods but can also extend into any branch of science. The adoption of the statistical techniques outlined in this paper will help speed the adoption of new high throughput phenotyping techniques by indicating when one should reject a new method, outright replace an old method or conditionally use a new method.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2011

Characterizing the Joint Effect of Diverse Test-Statistic Correlation Structures and Effect Size on False Discovery Rates in a Multiple-Comparison Study of Many Outcome Measures

In their 2009 Annals of Statistics paper, Gavrilov, Benjamini, and Sarkar report the results of a simulation assessing the robustness of their adaptive step-down procedure (GBS) for controlling the false discovery rate (FDR) when normally distributed test statistics are serially correlated. In this study we extend the investigation to the case of multiple comparisons involving correlated non-central t-statistics, in particular when several treatments or time periods are being compared to a control in a repeated-measures design with many dependent outcome measures. In addition, we consider several dependence structures other than serial correlation and illustrate how the FDR depends on the interaction between effect size and the type of correlation structure as indexed by Foerstner s distance metric from an identity. The relationship between the correlation matrix R of the original dependent variables and R~, the correlation matrix of associated t-statistics is also studied. In general R~ depends not only on R, but also on sample size and the signed effect sizes for the multiple comparisons.

Feiveson, Alan H.↗
DOE OSTI2022

Statistical Significance Testing for Mixed Priors: A Combined Bayesian and Frequentist Analysis

In many hypothesis testing applications, we have mixed priors, with well-motivated informative priors for some parameters but not for others. The Bayesian methodology uses the Bayes factor and is helpful for the informative priors, as it incorporates Occam’s razor via the multiplicity or trials factor in the look-elsewhere effect. However, if the prior is not known completely, the frequentist hypothesis test via the false-positive rate is a better approach, as it is less sensitive to the prior choice. We argue that when only partial prior information is available, it is best to combine the two methodologies by using the Bayes factor as a test statistic in the frequentist analysis. We show that the standard frequentist maximum likelihood-ratio test statistic corresponds to the Bayes factor with a non-informative Jeffrey’s prior. We also show that mixed priors increase the statistical power in frequentist analyses over the maximum likelihood test statistic. We develop an analytic formalism that does not require expensive simulations and generalize Wilks’ theorem beyond its usual regime of validity. In specific limits, the formalism reproduces existing expressions, such as the p-value of linear models and periodograms. We apply the formalism to an example of exoplanet transits, where multiplicity can be more than 10 7 . We show that our analytic expressions reproduce the $p$-values derived from numerical simulations. We offer an interpretation of our formalism based on the statistical mechanics. We introduce the counting of states in a continuous parameter space using the uncertainty volume as the quantum of the state. We show that both the $p$-value and Bayes factor can be expressed as an energy versus entropy competition.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1987

Statistical Tests of Reliability of NDE

Capabilities of advanced material-testing techniques analyzed. Collection of four reports illustrates statistical method for characterizing flaw-detecting capabilities of sophisticated nondestructive evaluation (NDE). Method used to determine reliability of several state-of-the-art NDE techniques for detecting failure-causing flaws in advanced ceramic materials considered for use in automobiles, airplanes, and space vehicles.

Baaklini, George Y.↗
NASA NTRS2012

A Statistical Test of Uniformity in Solar Cycle Indices

Several indices are used to characterize the solar activity cycle. Key among these are: the International Sunspot Number, the Group Sunspot Number, Sunspot Area, and 10.7 cm Radio Flux. A valuable aspect of these indices is the length of the record -- many decades and many (different) 11-year cycles. However, this valuable length-of-record attribute has an inherent problem in that it requires many different observers and observing systems. This can lead to non-uniformity in the datasets and subsequent erroneous conclusions about solar cycle behavior. The sunspot numbers are obtained by counting sunspot groups and individual sunspots on a daily basis. This suggests that the day-to-day and month-to-month variations in these numbers should follow Poisson Statistics and be proportional to the square-root of the sunspot numbers themselves. Examining the historical records of these indices indicates that this is indeed the case - even with Sunspot Area and 10.7 cm Radio Flux. The ratios of the RMS variations to the square-root of the indices themselves are relatively constant with little variation over the phase of each solar cycle or from small to large solar cycles. There are, however, important step-like changes in these ratios associated with changes in observer and/or observer system. Here we show how these variations can be used to construct more uniform datasets.

Hathaway David H.↗
DOE OSTI2026

Material Control & Accounting Statistical Test Modeling Supporting the Low Enriched Fuel Fabrication Facility Using F3M and MAPIT

This report covers the application of the TRi-structural ISOtropic (TRISO) fuel fabrication facility material control & accounting (MC&A) modeling capability developed by Sandia National Laboratories (SNL) under the U.S. Department of Energy (DOE) Materials Protection, Accounting, and Control Technologies (MPACT) program to support the development of MC&A approaches for the Low Enriched Fuel Fabrication Facility (LEFFF) at Los Alamos National Laboratory (LANL).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS1984

Reduction to Outside the Atmosphere and Statistical Tests Used in Geneva Photometry

Conditions for creating a precise photometric system are investigated. The analytical and discriminatory potentials of a photometry obviously result from the localization of the passbands in the spectrum; they do, however, also depend critically on the precision attained. This precision is the result of two different types of precautions. Two procedures which contribute in an efficient manner to achieving greater precision are examined. These two methods are known as hardware related precision and software related precision.

Rufener, F.↗
NASA NTRS1987

Statistical tests for closure of plate motion circuits

Two methods, one based on a chi-square test and the second on an F-ratio test, of testing for the plate motion circuit closures are described and evaluated. The chi-square test is used to evaluate goodness of fit, and it is assumed that the assigned errors are accurate estimates of the true errors in the data. The F-ratio test is used to compare variances of distributions, and it is assumed that the relative values of assigned error are accurate. The two methods are applied to the data of Minster and Jordan (1978) on the motion of the three plates that meet at the Galapagos Triple Junction, and the motion of the three plates that meet at the Indian Ocean Triple Junction. It is noted that the F-ratio plate circuit closure test is more useful than the chi-square test for identifying systematic misfits in data because the chi-square test overestimates the errors of plate motion data.

Gordon, Richard G.↗
NASA NTRS2002

The spectral correlation of functional clouds: a statistical test for theoretical models

We compute the spectral correlation function (SCF) of CO J=1-0 maps of moleculary cloud complexes. The SCF is a power law over approximately an order of magnitude in spatial separation in every map. The power law slope of the SCF, its normalization, and the spectral line width averaged over the whole map, are computed for all the observational maps.

turbulence kinematics↗