On selecting statistical data analysis techniques for space station applications
Statistical analysis of equipment selection for multipurpose scientific laboratory onboard space stations under economic and time constraints
Odell, P. L.↗
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Curve fitting and modeling with splines using statistical variable selection techniques
The successful application of statistical variable selection techniques to fit splines is demonstrated. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs, using the B-spline basis, were developed. The program for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.
Smith, P. L.↗
Fitting multidimensional splines using statistical variable selection techniques
This report demonstrates the successful application of statistical variable selection techniques to fit splines. Major emphasis is given to knot selection, but order determination is also discussed. Two FORTRAN backward elimination programs using the B-spline basis were developed, and the one for knot elimination is compared in detail with two other spline-fitting methods and several statistical software packages. An example is also given for the two-variable case using a tensor product basis, with a theoretical discussion of the difficulties of their use.
Smith, P. L.↗
Statistical Model Selection for TID Hardness Assurance
Radiation Hardness Assurance (RHA) methodologies against Total Ionizing Dose (TID) degradation impose rigorous statistical treatments for data from a part's Radiation Lot Acceptance Test (RLAT) and/or its historical performance. However, no similar methods exist for using "similarity" data - that is, data for similar parts fabricated in the same process as the part under qualification. This is despite the greater difficulty and potential risk in interpreting of similarity data. In this work, we develop methods to disentangle part-to-part, lot-to-lot and part-type-to-part-type variation. The methods we develop apply not just for qualification decisions, but also for quality control and detection of process changes and other "out-of-family" behavior. We begin by discussing the data used in ·the study and the challenges of developing a statistic providing a meaningful measure of degradation across multiple part types, each with its own performance specifications. We then develop analysis techniques and apply them to the different data sets.
Ladbury, R.↗
Statistical-mechanical selection of the shapes of disk galaxies
A new method is proposed for selecting steady state shapes of disk galaxies as 'most probable states' of a large number of stars, given only the total energy and total angular momentum. A partial differential equation is derived for the mean gravitational potential; it is closely related to the 'sinh-Poisson' equation for the mean-field description of a line vortex system or electrostatic guiding-center plasma. A 'water bag' approximation to the distribution function for bound stars renders the equation analytically tractable, but accurate solution of it may require numerical integration, in view of its general nonlinearity.
Montgomery, David↗
Selection of the Argentine indicator region
Determined from available Argentine crop statistics, selection of the Indicator Region was based on the highest wheat, corn, and soybean producing provinces, which were: Buenos Aires, Cordoba, Entre Rios, and Santa Fe. Each province in Argentina was examined for the availability of LANDSAT data; area, yield and production statistics; crop calendars; and other ancillary data. The Argentine Indicator Region is described.
Ramirez, C. J.↗
Investigation of statistical techniques to select optimal test levels for spacecraft vibration tests Final report, 1 Nov. 1969 - 31 Oct. 1970
Statistical techniques for selecting optimal test levels for vibration tests of spacecraft hardware
Maurer, J. R.↗
Development of natural environment criteria documents for aerospace vehicle and ground support development.
Design criteria documents for aerospace equipment for functioning under various environmental conditions, discussing environment selection, statistical data use and methods
Daniels, G. E.↗
Elemental composition of suspended particulates as functions of space and time in Cleveland, Ohio
An approach to the analysis of a very large elemental concentration data set. The particular data considered was generated by instrumental neutron activation and emission spectroscopy analyses of over 750 24-hour ambient air particulate samples collected at 16 sites in Cleveland, Ohio, during the 15 months from August 1971 thru October 1972. Examples are presented that show the use of multiple approaches to interpreting the data, including pairwise correlation statistics, selective data plotting and cluster analysis.
Neustadter, H. E.↗
Thermal- and plasma-induced molecular redistribution on the icy satellites
The molecular transport of condensed gas species across the surfaces of the icy satellites of Jupiter and Saturn is examined with the view of describing, in part, certain gross visual features associated with these bodies. Molecular redistribution induced by thermal sublimation and magnetospheric plasma-ion impact on satellites with negligible atmospheres is calculated by assuming that the molecules follow ballistic trajectories and by statistically selecting initial molecular velocities and points of origin. Erosion/deposition profiles so calculated are compared for a variety of satellite sizes and environments in order to understand the relative importance of sublimation and cold corotating plasma-ion- and fast plasma-ion-induced transport. The erosion/deposition profiles are used to discuss the appearance of a polar frost on Ganymede. A balance of magnetospheric-ion implantation and ion-induced molecular redistribution is used to discuss the observation of embedded SO2 and the darkening of the trailing side on Europa. Ion-induced molecular transport may also limit the deposition of SO2 frost in the polar regions of Io and may be a source of heavy particles in the Jovian and Saturnian magnetospheres.
Sieveka, E. M.↗
Learning process mapping heuristics under stochastic sampling overheads
A statistical method was developed previously for improving process mapping heuristics. The method systematically explores the space of possible heuristics under a specified time constraint. Its goal is to get the best possible heuristics while trading between the solution quality of the process mapping heuristics and their execution time. The statistical selection method is extended to take into consideration the variations in the amount of time used to evaluate heuristics on a problem instance. The improvement in performance is presented using the more realistic assumption along with some methods that alleviate the additional complexity.
Ieumwananonthachai, Arthur↗
Trend analysis for large solid rocket motors - A program level approach
This paper defines a program-level trend analysis effort that can be applied to large solid rocket motors. The effort is especially applicable to large segmented rocket motors such as the Space Transportation System's solid rocket boosters. Five types of trend analysis are discussed for different aspects of a rocket motor program, (performance, reliability, problem, supportability, and programmatic). Ideas are offered for implementing and performing a program-level trend analysis effort by giving suggestions for selecting computer capabilities, choosing parameters, selecting statistical processes, routine screening for trends, analyzing significant trends (for example, looking for related trends and determining if adverse trends are resolved), and reporting results of trend analysis. The use of program-level trending allows for the ability to easily transfer data between organizations and easily use the data to correlate trends from the various organizations to find causal relationships. Efficiency is enhanced from upper level management to the shop floor at vendor locations by using the same trend analysis software and methodology at all organizations.
Babbitt, Norman E., III↗
Identifying Optimal Temporal Scale for the Correlation of AOD and Ground Measurements of PM2.5 to Improve the Model Performance in a Real-time Air Quality Estimation System
Aerosol optical depth (AOD), an indirect estimate of particle matter using satellite observations, has shown great promise in improving estimates of PM 2.5 air quality surface. Currently, few studies have been conducted to explore the optimal way to apply AOD data to improve the model accuracy of PM 2.5 surface estimation in a real-time air quality system. We believe that two major aspects may be worthy of consideration in that area: 1) the approach to integrate satellite measurements with ground measurements in the pollution estimation, and 2) identification of an optimal temporal scale to calculate the correlation of AOD and ground measurements. This paper is focused on the second aspect on the identifying the optimal temporal scale to correlate AOD with PM2.5. Five following different temporal scales were chosen to evaluate their impact on the model performance: 1) within the last 3 days, 2) within the last 10 days, 3) within the last 30 days, 4) within the last 90 days, and 5) the time period with the highest correlation in a year. The model performance is evaluated for its accuracy, bias, and errors based on the following selected statistics: the Mean Bias, the Normalized Mean Bias, the Root Mean Square Error, Normalized Mean Error, and the Index of Agreement. This research shows that the model with the temporal scale of within the last 30 days displays the best model performance in this study area using 2004 and 2005 data sets.
Li, Hui↗
'Chain pooling' model selection as developed for the statistical analysis of a rotor burst protection experiment
A statistical decision procedure called chain pooling had been developed for model selection in fitting the results of a two-level fixed-effects full or fractional factorial experiment not having replication. The basic strategy included the use of one nominal level of significance for a preliminary test and a second nominal level of significance for the final test. The subject has been reexamined from the point of view of using as many as three successive statistical model deletion procedures in fitting the results of a single experiment. The investigation consisted of random number studies intended to simulate the results of a proposed aircraft turbine-engine rotor-burst-protection experiment. As a conservative approach, population model coefficients were chosen to represent a saturated 2 to the 4th power experiment with a distribution of parameter values unfavorable to the decision procedures. Three model selection strategies were developed.
Holms, A. G.↗
Analyzing Responses of Chemical Sensor Arrays
NASA is developing a third-generation electronic nose (ENose) capable of continuous monitoring of the International Space Station s cabin atmosphere for specific, harmful airborne contaminants. Previous generations of the ENose have been described in prior NASA Tech Briefs issues. Sensor selection is critical in both (prefabrication) sensor material selection and (post-fabrication) data analysis of the ENose, which detects several analytes that are difficult to detect, or that are at very low concentration ranges. Existing sensor selection approaches usually include limited statistical measures, where selectivity is more important but reliability and sensitivity are not of concern. When reliability and sensitivity can be major limiting factors in detecting target compounds reliably, the existing approach is not able to provide meaningful selection that will actually improve data analysis results. The approach and software reported here consider more statistical measures (factors) than existing approaches for a similar purpose. The result is a more balanced and robust sensor selection from a less than ideal sensor array. The software offers quick, flexible, optimal sensor selection and weighting for a variety of purposes without a time-consuming, iterative search by performing sensor calibrations to a known linear or nonlinear model, evaluating the individual sensor s statistics, scoring the individual sensor s overall performance, finding the best sensor array size to maximize class separation, finding optimal weights for the remaining sensor array, estimating limits of detection for the target compounds, evaluating fingerprint distance between group pairs, and finding the best event-detecting sensors.
Zhou, Hanying↗
A model for the simulation of atmospheric turbulence
A method that produces realistic simulations of atmospheric turbulence is developed and analyzed. The procedure makes use of a generalized spectral analysis, often called a proper orthogonal decomposition or the Karhunen-Loeve expansion. A set of criteria, emphasizing a realistic appearance, a correct spectral shape, and non-Gaussian statistics, is selected in order to evaluate the model turbulence. An actual turbulence record is analyzed in detail, providing both a standard for comparison and input statistics for the generalized spectral analysis. The simulation utilizes the eigenfunction-expansion procedure to produce preliminary time histories of the three velocity components simultaneously. It is found that important cross-statistical features are reasonably well-behaved.
Petersen, E. L.↗
Chain Pooling modeling selection as developed for the statistical analysis of a rotor burst protection experiment
As many as three iterated statistical model deletion procedures were considered for an experiment. Population model coefficients were chosen to simulate a saturated 2 to the 4th power experiment having an unfavorable distribution of parameter values. Using random number studies, three model selection strategies were developed, namely, (1) a strategy to be used in anticipation of large coefficients of variation, approximately 65 percent, (2) a strategy to be sued in anticipation of small coefficients of variation, 4 percent or less, and (3) a security regret strategy to be used in the absence of such prior knowledge.
Holms, A. G.↗
System and method for progressive band selection for hyperspectral images
Disclosed herein are systems, methods, and non-transitory computer-readable storage media for progressive band selection for hyperspectral images. A system having module configured to control a processor to practice the method calculates a virtual dimensionality of a hyperspectral image having multiple bands to determine a quantity Q of how many bands are needed for a threshold level of information, ranks each band based on a statistical measure, selects Q bands from the multiple bands to generate a subset of bands based on the virtual dimensionality, and generates a reduced image based on the subset of bands. This approach can create reduced datasets of full hyperspectral images tailored for individual applications. The system uses a metric specific to a target application to rank the image bands, and then selects the most useful bands. The number of bands selected can be specified manually or calculated from the hyperspectral image's virtual dimensionality.
Fisher, Kevin↗