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NASA Scientific and Technical Aerospace Reports

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incorporating simulation-based optimization (<strong>and</strong>, in particular, ordinal optimization) into dynamic optimization problems. In<br />

support of this task, progress was made on new sampling methods for Markov Decision Processes (MDPs), a new time<br />

aggregation approach for MDPs, simulation-based methods for weighted cost-to-go MDPs, approaches to proving the<br />

exponential convergence rate of ordinal comparisons, approximate receding horizon approaches to MDPs <strong>and</strong> Markov games,<br />

<strong>and</strong> new classes of stochastic approximation algorithms. In support of the second major task that involved estimation <strong>and</strong><br />

control algorithms for dynamic hierarchical <strong>and</strong> graphical models, a variety of algorithms <strong>and</strong> analytical tools were developed<br />

for models on graphs with loops that exploit embedded loop-free structure. These algorithms offer the potential of significantly<br />

enhanced solutions to a variety of optimization problems critical to the Air Force. Another major task in the proposal involved<br />

risk-sensitive estimation <strong>and</strong> control. In support of this task, a new filtering scheme for the risk-sensitive state estimation of<br />

partially observed Markov chains was introduced <strong>and</strong> analyzed.<br />

DTIC<br />

Markov Processes; Simulation<br />

20040112005 <strong>NASA</strong> Langley Research Center, Hampton, VA, USA<br />

Linear Least Squares for Correlated Data<br />

Dean, Edwin B.; [1988]; 10 pp.; In English; Tenth Annual International Conference for the International Society of Parametric<br />

Analysts, 25-27 Jul. 1988, Brighton, UK; Original contains black <strong>and</strong> white illustrations; No Copyright; Avail: CASI; A02,<br />

Hardcopy<br />

Throughout the literature authors have consistently discussed the suspicion that regression results were less than<br />

satisfactory when the independent variables were correlated. Camm, Gulledge, <strong>and</strong> Womer, <strong>and</strong> Womer <strong>and</strong> Marcotte provide<br />

excellent applied examples of these concerns. Many authors have obtained partial solutions for this problem as discussed by<br />

Womer <strong>and</strong> Marcotte <strong>and</strong> Wonnacott <strong>and</strong> Wonnacott, which result in generalized least squares algorithms to solve restrictive<br />

cases. This paper presents a simple but relatively general multivariate method for obtaining linear least squares coefficients<br />

which are free of the statistical distortion created by correlated independent variables.<br />

Derived from text<br />

Multivariate Statistical Analysis; Regression Analysis; Independent Variables; Algorithms<br />

20040121013 Defence Science <strong>and</strong> Technology Organisation, Edinburgh, Australia<br />

Comparative Descriptive Statistics of Skewed Probability Distributions<br />

Fewell, M. P.; July 2004; 50 pp.; In English; Original contains black <strong>and</strong> white illustrations<br />

Report No.(s): DSTO-TR-1596; DODA-AR-013-136; Copyright; Avail: Other Sources<br />

This report is a brief h<strong>and</strong>book on the comparative descriptive statistics of a wide variety of skewed probability<br />

distributions, both continuous <strong>and</strong> discrete. The aim is to facilitate the comparison of different distributions, for use where<br />

r<strong>and</strong>om variables are employed without any firm information on their distribution. In this situation, it is of interest to look for<br />

sensitivity to the distribution chosen. This can best be done by running the model with a variety of distributions, which then<br />

raises the question of how to compare distributions. This work advocates the use of moments <strong>and</strong> presents the requisite<br />

equations. As obvious as this approach may appear, many of the equations do not seem to have been published previously <strong>and</strong><br />

some of the results are apparently wholly new. A total of 18 distributions are treated in detail, including all of the most<br />

commonly used skewed probability distributions.<br />

Author<br />

Probability Distribution Functions; R<strong>and</strong>om Variables<br />

66<br />

SYSTEMS ANALYSIS AND OPERATIONS RESEARCH<br />

Includes mathematical modeling of systems; network analysis; mathematical programming; decision theory; <strong>and</strong> game theory.<br />

20040111454 NATO Consultation, Comm<strong>and</strong>, <strong>and</strong> Control Agency, Brussels<br />

Analysis <strong>and</strong> Evaluation of the Immediate Reaction Task Force (L<strong>and</strong>) Comm<strong>and</strong> <strong>and</strong> Control Concept: Applying the<br />

COBP<br />

Lambert, Nicholas J.; C<strong>and</strong>an, Umit; Dec. 2003; 56 pp.; In English; Original contains color illustrations<br />

Report No.(s): AD-A425336; No Copyright; Avail: CASI; A04, Hardcopy<br />

No abstract available<br />

Comm<strong>and</strong> <strong>and</strong> Control; Evaluation; Military Operations; North Atlantic Treaty Organization (NATO); System Effectiveness<br />

268

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