The generation of random numbers on the IBM 360/44
A summary is presented of the generation and testing of random numbers on the IBM 360/44 computer. Various generators and statistical tests are considered.
Speed, F. M.↗
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Results for “TEST STATISTIC”
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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Implications for high speed research: The relationship between sonic boom signature distortion and atmospheric turbulence
In this study there were two primary tasks. The first was to develop an algorithm for quantifying the distortion in a sonic boom. Such an algorithm should be somewhat automatic, with minimal human intervention. Once the algorithm was developed, it was used to test the hypothesis that the cause of a sonic boom distortion was due to atmospheric turbulence. This hypothesis testing was the second task. Using readily available sonic boom data, we statistically tested whether there was a correlation between the sonic boom distortion and the distance a boom traveled through atmospheric turbulence.
Sparrow, Victor W.↗
A Statistical Filtering Approach for Gravity Recovery and Climate Experiment (GRACE) Gravity Data
We describe and analyze a statistical filtering approach for GRACE data that uses a parametrized model for the temporal evolution of the GRACE coefficients. After least-squares adjustment, a statistical test is performed to assess the significance of the estimated parameters. If the test is passed, the parameters are used by the filter in the reconstruction of the field; otherwise they are rejected. The test is performed, and the filter is formed, separately for annual components of the model and the trend. This new approach is distinct from Gaussian smoothing since it uses the data themselves to test for specific components of the time-varying gravity field. The statistical filter appears inherently to remove most of the "stripes" present in the GRACE fields, although destriping the fields prior to filtering seems to help the trend recovery. We demonstrate that the statistical filter produces reasonable maps for the annual components and trend. We furthermore assess the statistical filter for the annual components using ground-based GPS data in South America by assuming that the annual component of the gravity signal is associated only with groundwater storage. The un-destriped, statistically filtered field has a X2 value relative to the GPS data consistent with the best result from smoothing. In the space domain, the statistical filters are qualitatively similar to Gaussian smoothing. Unlike Gaussian smoothing, however, the statistical filter has significant sidelobes, including large negative sidelobes on the north-south axis, potentially revealing information on the errors, and the correlations among the errors, for the GRACE coefficients.
Davis. J. L.↗
Defining window-boundaries for genomic analyses using smoothing spline techniques
High-density genomic data is often analyzed by combining information over windows of adjacent markers. Interpretation of data grouped in windows versus at individual locations may increase statistical power, simplify computation, reduce sampling noise, and reduce the total number of tests performed. However, use of adjacent marker information can result in over- or under-smoothing, undesirable window boundary specifications, or highly correlated test statistics. We introduce a method for defining windows based on statistically guided breakpoints in the data, as a foundation for the analysis of multiple adjacent data points. This method involves first fitting a cubic smoothing spline to the data and then identifying the inflection points of the fitted spline, which serve as the boundaries of adjacent windows. This technique does not require prior knowledge of linkage disequilibrium, and therefore can be applied to data collected from individual or pooled sequencing experiments. Moreover, in contrast to existing methods, an arbitrary choice of window size is not necessary, since these are determined empirically and allowed to vary along the genome.
59 BASIC BIOLOGICAL SCIENCES↗
A novel framework for increasing research transparency: Exploring the connection between diversity and innovation
A split sample/dual method research protocol is demonstrated to increase transparency while reducing the probability of false discovery. We apply the protocol to examine whether diversity in ownership teams increases or decreases the likelihood of a firm reporting a novel innovation using data from the 2018 United States Census Bureau’s Annual Business Survey. Transparency is increased in three ways: 1) all specification testing and identifying potentially productive models is done in an exploratory subsample that 2) preserves the validity of hypothesis test statistics fromde novoestimation in the holdout confirmatory sample with 3) all findings publicly documented in an earlier registered report and in this journal publication. Bayesian estimation procedures that leverage information from the exploratory stage included in the confirmatory stage estimation replace traditional frequentist null hypothesis significance testing. In addition to increasing statistical power by using information from the full sample, Bayesian methods directly estimate a probability distribution for the magnitude of an effect, allowing much richer inference. Estimated magnitudes of diversity along academic discipline, race, ethnicity, and foreign-born status dimensions are positively associated with innovation. A maximally diverse ownership team on these dimensions would be roughly six times more likely to report new-to-market innovation than a homophilic team.
Science & Technology - Other Topics↗
Detecting anomalies in CMB maps: a new method
Ever since WMAP announced its first results, different analyses have shown that there is weak evidence for several large-scale anomalies in the CMB data. While the evidence for each anomaly appears to be weak, the fact that there are multiple seemingly unrelated anomalies makes it difficult to account for them via a single statistical fluke. So, one is led to considering a combination of these anomalies. But, if we ''hand-pick'' the anomalies (test statistics) to consider, we are making an a posteriori choice. In this article, we propose two statistics that do not suffer from this problem. The statistics are linear and quadratic combinations of the a{sub ℓ m}'s with random co-efficients, and they test the null hypothesis that the a{sub ℓ m}'s are independent, normally-distributed, zero-mean random variables with an m-independent variance. The motivation for considering multiple modes is this: because most physical models that lead to large-scale anomalies result in coupling multiple ℓ and m modes, the ''coherence'' of this coupling should get enhanced if a combination of different modes is considered. In this sense, the statistics are thus much more generic than those that have been hitherto considered in literature. Using fiducial data, we demonstrate that the method works and discuss how it can be used with actual CMB data to make quite general statements about the incompatibility of the data with the null hypothesis.
79 ASTRONOMY AND ASTROPHYSICS↗
Performance analysis of Wald-statistic based network detection methods for radiation sources
There have been increasingly large deployments of radiation detection networks that require computationally fast algorithms to produce prompt results over ad-hoc sub-networks of mobile devices, such as smart-phones. These algorithms are in sharp contrast to complex network algorithms that necessitate all measurements to be sent to powerful central servers. In this work, at individual sensors, we employ Wald-statistic based detection algorithms which are computationally very fast, and are implemented as one of three Z-tests and four chi-square tests. At fusion center, we apply the K-out-of-N fusion to combine the sensors hard decisions. We characterize the performance of detection methods by deriving analytical expressions for the distributions of underlying test statistics, and by analyzing the fusion performances in terms of K, N, and the false-alarm rates of individual detectors. We experimentally validate our methods using measurements from indoor and outdoor characterization tests of the Intelligence Radiation Sensors Systems (IRSS) program. In particular, utilizing the outdoor measurements, we construct two important real-life scenarios, boundary surveillance and portal monitoring, and present the results of our algorithms.
Sen, Satyabrata↗
Characterization of Space Shuttle Reusable Rocket Motor Static Test Stand Thrust Measurements
Space Shuttle Reusable Solid Rocket Motors (RSRM) are static tested at two ATK Thiokol Propulsion facilities in Utah, T-24 and T-97. The newer T-97 static test facility was recently upgraded to allow thrust measurement capability. All previous static test motor thrust measurements have been taken at T-24; data from these tests were used to characterize thrust parameters and requirement limits for flight motors. Validation of the new T-97 thrust measurement system is required prior to use for official RSRM performance assessments. Since thrust cannot be measured on RSRM flight motors, flight motor measured chamber pressure and a nominal thrust-to-pressure relationship (based on static test motor thrust and pressure measurements) are used to reconstruct flight motor performance. Historical static test and flight motor performance data are used in conjunction with production subscale test data to predict RSRM performance. The predicted motor performance is provided to support Space Shuttle trajectory and system loads analyses. Therefore, an accurate nominal thrust-to-pressure (F/P) relationship is critical for accurate RSRM flight motor performance and Space Shuttle analyses. Flight Support Motors (FSM) 7, 8, and 9 provided thrust data for the validation of the T-97 thrust measurement system. The T-97 thrust data were analyzed and compared to thrust previously measured at T-24 to verify measured thrust data and identify any test-stand bias. The T-97 FIP data were consistent and within the T-24 static test statistical family expectation. The FSMs 7-9 thrust data met all NASA contract requirements, and the test stand is now verified for future thrust measurements.
Mart L. Cook↗
Image Distinguishability Analysis Testing Through Principal Components and Its Application to Hot Spot Scale Invariance
Hot spots are spatial regions of intense energy localization that govern initiation of secondary high explosives. Studies that characterize or compare simulated hot spots are frequently either qualitatively descriptive or resort to quantitative distribution functions that neglect stochastic variations and spatial correlations—effects that are also neglected in common comparison tests like the Kolmogorov–Smirnov test. To this end, we develop an image distinguishability analysis (IDA) test based on principal component (PC) analysis that makes pixel-by-pixel comparisons between small, for example, O(<10), image data sets. The IDA test makes comparisons through a generalized distance metric in the PC space and a test statistic that is derived to calculate mathematical equation-values. Here, we derive a statistical distribution and criticality criterion to determine whether images are distinguishable from established baselines. We apply the IDA test on images generated from molecular dynamics simulations of hot spots from pore collapse in TATB to assess scale invariance in the complex patterns of hot spots that form in a representative high explosive crystal. The IDA test shows that TATB hot spot spatial temperature fields and their derived temperature histograms exhibit scale-invariant features over specific intervals of shock orientation, strength, and initial pore diameter. However, the IDA test also shows that qualitatively different conclusions regarding invariance can be reached depending on whether the hot spot is treated as a spatially correlated field as opposed to a distribution function that lacks spatial information.
organic↗
"Weekend-effect" evidence for intensification of storms by pollution over U.S.
Aerosols change the way precipitating clouds evolve, due to their effect on condensation and ice formation. The net effect of aerosols on precipitation varies depending on the local environment and synoptic situation, the types of aerosols, and also on how far downstream one looks for effects. Repeated experiments with controlled release of aerosols would be helpful in unraveling how aerosols affect precipitation. The weekly variation in human activity may provide just such a set of experiments. Using the rainfall estimates from the passive microwave instrument on the Tropical Rainfall Measuring Mission (TRMM), which has been orbiting for over eight years and can view areas as far north as about 40 degs, we find that there is indeed a weekly variation in summer (JJA) rainfall over the southeastern U.S. land area, with the average rain rate peaking in the middle of the week (Tue-Thu). Rainfall over nearby oceanic areas, on the other hand, seems to peak on weekends. A bootstrap statistical test indicates that the variations are unlikely to be due to chance. Physically related weekly variations in the statistics of ground-based measurements and model reanalysis data are found. The midweek peak in rainfall over land coincides with the well documented midweek peak in pollution around much of the U.S., and is unlikely to be due to other weekly variations in human influence. The midweek increase is also unlikely to be a consequence of the radiative heating or cooling of the atmosphere by the aerosols.
Bell, T. L.↗
An Assessment of Actual and Potential Building Climate Zone Change and Variability From the Last 30 Years Through 2100 Using NASA's MERRA and CMIP5 Simulations
Background: In the US, residential and commercial building infrastructure combined consumes about 40% of total energy usage and emits about 39% of total CO2 emission (DOE/EIA "Annual Energy Outlook 2013"). Building codes, as used by local and state enforcement entities are typically tied to the dominant climate within an enforcement jurisdiction classified according to various climate zones. These climate zones are based upon a 30-year average of local surface observations and are developed by DOE and ASHRAE. Establishing the current variability and potential changes to future building climate zones is very important for increasing the energy efficiency of buildings and reducing energy costs and emissions in the future. Objectives: This paper demonstrates the usefulness of using NASA's Modern Era Retrospective-analysis for Research and Applications (MERRA) atmospheric data assimilation to derive the DOE/ASHRAE building climate zone maps and then using MERRA to define the last 30 years of variability in climate zones for the Continental US. An atmospheric assimilation is a global atmospheric model optimized to satellite, atmospheric and surface in situ measurements. Using MERRA as a baseline, we then evaluate the latest Climate Model Inter-comparison Project (CMIP) climate model Version 5 runs to assess potential variability in future climate zones under various assumptions. Methods: We derive DOE/ASHRAE building climate zones using surface and temperature data products from MERRA. We assess these zones using the uncertainties derived by comparison to surface measurements. Using statistical tests, we evaluate variability of the climate zones in time and assess areas in the continental US for statistically significant trends by region. CMIP 5 produced a data base of over two dozen detailed climate model runs under various greenhouse gas forcing assumptions. We evaluate the variation in building climate zones for 3 different decades using an ensemble and quartile statistics to provide an assessment of potential building climate zone changes relative to the uncertainties demonstrated using MERRA. Findings and Conclusions: These results show that there is a statistically significant increase in the area covered by warmer climate zones and a tendency for a reduction of area in colder climate zones in some limited regions. The CMIP analysis shows that models vary from relatively little building climate zone change for the least sensitive and conservation assumptions to a warming of at most 3 zones for certain areas, particularly the north central US by the end of the 21st century.
Stackhouse, Paul W., Jr.↗
Detection of Digital Elevation Model Errors Using X-band Weather Radar
Flight in Instrument Meteorological Conditions requires pilots to manipulate flight controls while referring to a Primary Flight Display. The Primary Flight Display indicates aircraft attitude along with, in some cases, many other state variables such as altitude, speed, and guidance cues. Synthetic Vision Systems have been proposed that overlay the traditional information provided on Primary Flight Displays onto a scene depicting the location of terrain and other geo-spatial features.Terrain models used by these displays must have sufficient quality to avoid providing misleading information. This paper describes how X-band radar measurements can be used as part of a monitor, and/or maintenance system, to quantify the integrity of terrain models that are used by systems such as Synthetic Vision. Terrain shadowing effects, as seen by the radar, are compared in a statistical manner against estimated shadow feature elements extracted from the stored terrain model from the perspective of the airborne observer. A test statistic is defined that enables detection of errors as small as the range resolution of the radar. Experimental results obtained from two aircraft platforms hosting certified commercial-off-the-shelf X-band radars test the premise and illustrate its potential.
Young, Steven D.↗
Grid-based minimization at scale: Feldman-Cousins corrections for light sterile neutrino search
High Energy Physics (HEP) experiments generally employ sophisticated statistical methods to present results in searches of new physics. In the problem of searching for sterile neutrinos, likelihood ratio tests are applied to short-baseline neutrino oscillation experiments to construct confidence intervals for the parameters of interest. The test statistics of the form Δχ2 is often used to form the confidence intervals, however, this approach can lead to statistical inaccuracies due to the small signal rate in the region-of-interest. In this paper, we present a computational model for the computationally expensive Feldman-Cousins corrections to construct a statistically accurate confidence interval for neutrino oscillation analysis. The program performs a grid-based minimization over oscillation parameters and is written in C++. Our algorithms make use of vectorization through Eigen3, yielding a single-core speed-up of 350 compared to the original implementation, and achieve MPI data parallelism by employing DIY. We demonstrate the strong scaling of the application at High-Performance Computing (HPC) sites. We utilize HDF5 along with HighFive to write the results of the calculation to file.
Wospakrik, Marianette↗
A rule-based software test data generator
Rule-based software test data generation is proposed as an alternative to either path/predicate analysis or random data generation. A prototype rule-based test data generator for Ada programs is constructed and compared to a random test data generator. Four Ada procedures are used in the comparison. Approximately 2000 rule-based test cases and 100,000 randomly generated test cases are automatically generated and executed. The success of the two methods is compared using standard coverage metrics. Simple statistical tests showing that even the primitive rule-based test data generation prototype is significantly better than random data generation are performed. This result demonstrates that rule-based test data generation is feasible and shows great promise in assisting test engineers, especially when the rule base is developed further.
Deason, William H.↗
Safeguarding a Lunar Rover with Wald's Sequential Probability Ratio Test
The virtual bumper is a safeguarding mechanism for autonomous and remotely operated robots. In this paper we take a new approach to the virtual bumper system by using an old statistical test. By using a modified version of Wald's sequential probability ratio test we demonstrate that we can reduce the number of false positive reported by the virtual bumper, thereby saving valuable mission time. We use the concept of sequential probability ratio to control vehicle speed in the presence of possible obstacles in order to increase certainty about whether or not obstacles are present. Our new algorithm reduces the chances of collision by approximately 98 relative to traditional virtual bumper safeguarding without speed control.
safeguarding↗
First Searches for Axions and Axionlike Particles with the LUX Experiment
The first searches for axions and axionlike particles with the Large Underground Xenon experiment are presented. Under the assumption of an axioelectric interaction in xenon, the coupling constant between axions and electrons g Ae is tested using data collected in 2013 with an exposure totaling 95 live days ×118 kg. A double-sided, profile likelihood ratio statistic test excludes g Ae larger than 3.5 × 10 –12 (90% C.L.) for solar axions. Assuming the Dine-Fischler-Srednicki-Zhitnitsky theoretical description, the upper limit in coupling corresponds to an upper limit on axion mass of 0.12 eV/c 2 , while for the Kim-Shifman-Vainshtein-Zhakharov description masses above 36.6 eV/c 2 are excluded. For galactic axionlike particles, values of g Ae larger than 4.2 × 10 –13 are excluded for particle masses in the range 1–16 keV/c 2 . As a result, these are the most stringent constraints to date for these interactions.
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
SU-F-I-80: Correction for Bias in a Channelized Hotelling Model Observer Caused by Temporally Variable Non-Stationary Noise
Purpose: Application of a channelized Hotelling model observer (CHO) over a wide range of x-ray angiography detector target dose (DTD) levels demonstrated substantial bias for conditions yielding low detectability indices (d’), including low DTD and small test objects. The purpose of this work was to develop theory and methods to correct this bias. Methods: A hypothesis was developed wherein the measured detectability index (d’b) for a known test object is positively biased by temporally variable non-stationary noise in the images. Hotelling’s T2 test statistic provided the foundation for a mathematical theory which accounts for independent contributions to the measured d’b value from both the test object (d’o) and non-stationary noise (d’ns). Experimental methods were developed to directly estimate d’o by determining d’ns and subtracting it from d’b, in accordance with the theory. Specifically, d’ns was determined from two sets of images from which the traditional test object was withheld. This method was applied to angiography images with DTD levels in the range 0 to 240 nGy and for disk-shaped iodine-based contrast targets with diameters 0.5 to 4.0 mm. Results: Bias in d’ was evidenced by d’b values which exceeded values expected from a quantum limited imaging system and decreasing object size and DTD. d’ns increased with decreasing DTD, reaching a maximum of 2.6 for DTD = 0. Bias-corrected d’o estimates demonstrated sub-quantum limited performance of the x-ray angiography for low DTD. Findings demonstrated that the source of non-stationary noise was detector electronic readout noise. Conclusion: Theory and methods to estimate and correct bias in CHO measurements from temporally variable non-stationary noise were presented. The temporal non-stationary noise was shown to be due to electronic readout noise. This method facilitates accurate estimates of d’ values over a large range of object size and detector target dose.
60 APPLIED LIFE SCIENCES↗
Simulation of deep one- and two-dimensional redshift surveys
It is shown that slice or pencil-beam redshift surveys of galaxies can be simulated in a box with nonequal sides. This method saves a lot of computer time and memory while providing essentially the same results as from whole-cube simulations. A 2457.6/h Mpc-long rod (out to a redshift z = 0.58 in two opposite directions) is simulated using the standard biased cold dark matter model as an example to mimic the recent deep pencil-beam surveys by Broadhurst et al. (1990). The structures (spikes) seen in these simulated samples occur when the narrow pencil-beam pierces walls, filaments, and clusters appearing randomly along the line-of-sight. A statistical test for goodness of fit to a periodic lattice has been applied to the observations and the simulations. It is found that the statistical significance level (P = 15.4 percent) is not strong enough to reject the null hypothesis that the observations and the simulations were drawn at random from the same set.
Park, Changbom↗