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At least 55 records · Page 3

Geopositional Statistical Methods

RMSE based methods distort circular error estimates (up to 50% overestimation). The empirical approach is the only statistically unbiased estimator offered. Ager modification to Shultz approach is nearly unbiased, but cumbersome. All methods hover around 20% uncertainty (@ 95% confidence) for low geopositional bias error estimates. This requires careful consideration in assessment of higher accuracy products.

Ross, Kenton

A statistical method for treating molecular line opacities

A method for treating atomic and molecular line opacities in cool stellar atmospheres by a statistical opacity sampling is investigated. Under the usual assumptions of plane-parallel geometry, radiative equilibrium, hydrostatic equilibrium, and LTE, each radiative quantity is computed monochromatically at each chosen frequency and depth without any averaging of the opacity. The number of frequencies needed to allow an accurate integration of the energy flux over a given spectral interval is investigated as a function of depth, including opacity for both CN and C2. This method is extended to the calculation of a model atmosphere of a star, and the effect of the number and placement of frequency points is studied. The method is applied to treating molecular lines of CO, C2, and CN in a cool carbon star. Significant advantages of the opacity sampling method are its flexibility, which permits computation of models having arbitrary variations of chemical composition and of opacity with wavelength and depth, and generalizability to include departures from LTE.

Sneden, C.

Statistical methods for efficient design of community surveys of response to noise: Random coefficients regression models

Research studies of residents' responses to noise consist of interviews with samples of individuals who are drawn from a number of different compact study areas. The statistical techniques developed provide a basis for those sample design decisions. These techniques are suitable for a wide range of sample survey applications. A sample may consist of a random sample of residents selected from a sample of compact study areas, or in a more complex design, of a sample of residents selected from a sample of larger areas (e.g., cities). The techniques may be applied to estimates of the effects on annoyance of noise level, numbers of noise events, the time-of-day of the events, ambient noise levels, or other factors. Methods are provided for determining, in advance, how accurately these effects can be estimated for different sample sizes and study designs. Using a simple cost function, they also provide for optimum allocation of the sample across the stages of the design for estimating these effects. These techniques are developed via a regression model in which the regression coefficients are assumed to be random, with components of variance associated with the various stages of a multi-stage sample design.

Tomberlin, T. J.

Statistical Methods for Rapid Aerothermal Analysis and Design Technology: Validation

The cost and safety goals for NASA s next generation of reusable launch vehicle (RLV) will require that rapid high-fidelity aerothermodynamic design tools be used early in the design cycle. To meet these requirements, it is desirable to identify adequate statistical models that quantify and improve the accuracy, extend the applicability, and enable combined analyses using existing prediction tools. The initial research work focused on establishing suitable candidate models for these purposes. The second phase is focused on assessing the performance of these models to accurately predict the heat rate for a given candidate data set. This validation work compared models and methods that may be useful in predicting the heat rate.

DePriest, Douglas

Statistical Methods for Rapid Aerothermal Analysis and Design Technology

The cost and safety goals for NASA's next generation of reusable launch vehicle (RLV) will require that rapid high-fidelity aerothermodynamic design tools be used early in the design cycle. To meet these requirements, it is desirable to establish statistical models that quantify and improve the accuracy, extend the applicability, and enable combined analyses using existing prediction tools. The research work was focused on establishing the suitable mathematical/statistical models for these purposes. It is anticipated that the resulting models can be incorporated into a software tool to provide rapid, variable-fidelity, aerothermal environments to predict heating along an arbitrary trajectory. This work will support development of an integrated design tool to perform automated thermal protection system (TPS) sizing and material selection.

Morgan, Carolyn

Statistical method for the prediction of matching results in spectral file searching

In file-search techniques, the distribution of mismatches quantitatively measures the fit of a particular unknown against a given library. A simple theoretical method is developed to predict, a priori, this distribution. With this procedure, for any unknown code and library, the mean number of mismatches can be calculated exactly. For a given library and coding scheme, the mismatch distribution for most unknown codes closely follows a common curve which is easily calculated from statistical properties of the library. When this common curve is normalized to a constant mean, the observed matching behavior is well predicted. The theory should permit the user to more clearly assess the effects of errors on file search performance and suggest techniques by which recognition performance may be optimized.

Grotch, S. L.

Data Analysis & Statistical Methods for Command File Errors

This paper explains current work on modeling for managing the risk of command file errors. It is focused on analyzing actual data from a JPL spaceflight mission to build models for evaluating and predicting error rates as a function of several key variables. We constructed a rich dataset by considering the number of errors, the number of files radiated, including the number commands and blocks in each file, as well as subjective estimates of workload and operational novelty. We have assessed these data using different curve fitting and distribution fitting techniques, such as multiple regression analysis, and maximum likelihood estimation to see how much of the variability in the error rates can be explained with these. We have also used goodness of fit testing strategies and principal component analysis to further assess our data. Finally, we constructed a model of expected error rates based on the what these statistics bore out as critical drivers to the error rate. This model allows project management to evaluate the error rate against a theoretically expected rate as well as anticipate future error rates.

Correlation Analysis

Description of statistical methods and a routine for determining the parameters of a model in processing experimental results

A computer routine is suggested for selecting the optimum parameters of a theoretical model and determining the errors in them due to errors in physical measurements and for evaluating the conformity of theory with the experiment. The paper describes the specification sequence for the input data and the format of the calculation results. Sample printouts are appended.

Usikov, D. A.

A statistical method to sense sea surface temperature from the Nimbus-7 scanning multichannel microwave radiometer

Among the five channels in the Scanning Multichannel Microwave Radiometer (SMMR), the brightness temperature measured at 6.6 GHz vertical polarization is least affected by the atmospheric water vapor and liquid water in clouds or rain. Furthermore, as the undisturbed sea surface emissivity at 6.6 GHz is nearly constant over the temperature range 275 to 300 K, this channel has the best sensitivity to sea surface temperature (SST). The 6.6 GHz channel on SMMR is specifically chosen for these reasons to measure SST.

Prabhakara, C.

Evaluation of alpha-SiC sintering using statistical methods

The effect of time and temperature on the density and strength of alpha-SiC was studied and mathematically modeled using a central composite experimental design. A sintering temperature of 2150 C for 1.7 h maximized the flexural strength and densification values. However, temperatures above 2200 C promoted abnormal grain growth, with resulting appreciable decreases in strength. Flexural strength increased exponentially with increasing density for specimens with densities less than or equal to 92 percent of theoretical.

Hurst, J. B.