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Information Technology Laboratory /Statistical Engineering Division

Gaithersburg Group

The Gaithersburg Group of the Statistical Engineering Division focuses on collaborations with NIST scientists in the Gaithersburg, Maryland, campus.

The Gaithersburg Group focuses on collaborations with NIST scientists in the Gaithersburg, Maryland, campus, with emphasis on NIST's Special Programs (including greenhouse gases and law enforcement standards), IMS projects (e.g., Optical Medical Imaging, Shape Metrology), statistical modeling and data analysis for NIST Standard Reference Materials, experimental design, exploratory data analysis, and statistical modeling and inference supporting scientific discovery and technology development, as well as education and training.

Highlights

Statistical Metrology Short Courses - Staff members of the Statistical Engineering Division regularly offer short courses on uncertainty analysis, design of experiments, and other topics in statistical metrology. Short courses are offered at NIST, at conferences open to the public, and for other government agencies.

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News and Updates

Projects and Programs

Hawkes intensities and QQ plots for MLE fits for several stairs

A Point Process Model for Evacuation Flows: The Hawkes Mode

Ongoing
Results from a case study of evacuations of 14 office and residential buildings in the United States led us to model occupant exit times as a Hawkes point process, N(t). N(t) the number of evacuee exits in the time interval (0,t]. Because the Hawkes model is self-similar, human to human interaction

Building Joint Sealant Service Life Prediction

Ongoing
The primary building sealant problem is that no method exists to provide high quality data for elucidating the relative importance of the k = 4 major weathering factors: X1: temperature, X2: humidity, X3: ultra-violet radiation, and X4: mechanical loading(and interactions) on the change in pre

Cement Characteristics by Direct Phase Assessment

Ongoing
DESCRIPTION: The major research goal is the accurate prediction of field performance metrics from accurate characterization of mineralogical composition and texture. Compounding characterization and prediction problems is the widespread reliance since the 1930's on the Bogue estimates of composition

Comparison of Internet Congestion-Control Algorithms

Complex systems are generically characterized by a large number of factors and a large number of potential responses, hence statistical questions immediately present themselves as to 1. What should be measured? 2. What experiment design should be used to generate content-full data? 3. How should

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Awards

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