Engineering topics

Terrell, G. R.

Publications and source records attributed to Terrell, G. R..

6 records

NASA NTRS1981

An algorithm for the rapid location of an extreme of a function subject only to geometric restrictions

The requirements of symmetry and convexity in the application of algorithms for the minimization or maximization of a function are discussed. It is argued that if a function of a single variable is convex and symmetric in a neighborhood of an extremum, the extremum may be approximated to the precision that increases by at least a power of two per functional evaluation. The procedure may be used to drive a complex optimization procedure in the multivariate area estimation problem encountered in remote sensing.

Terrell, G. R.↗

NASA NTRS1980

Proportion estimation using prior cluster purities

The prior distribution of CLASSY component purities is studied, and this information incorporated into maximum likelihood crop proportion estimators. The method is tested on Transition Year spring small grain segments.

Terrell, G. R.↗

NASA NTRS1980

Minimum variance geographic sampling

Resource inventories require samples with geographical scatter, sometimes not as widely spaced as would be hoped. A simple model of correlation over distances is used to create a minimum variance unbiased estimate population means. The fitting procedure is illustrated from data used to estimate Missouri corn acreage.

Terrell, G. R.↗

NASA NTRS1980

A note on the generation of Poisson-distributed random numbers with large mean

There are no author-identified significant results in this report.

Terrell, G. R.↗

NASA NTRS1980

Evaluating the Use of Analyst Labels in Maximum Likelihood Cluster Proportion Estimation

There are no author-identified significant results in this report.

Lennington, R. K.↗

NASA NTRS1980

A bound for the smoothing parameter in certain well-known nonparametric density estimators

Two classes of nonparametric density estimators, the histogram and the kernel estimator, both require a choice of smoothing parameter, or 'window width'. The optimum choice of this parameter is in general very difficult. An upper bound to the choices that depends only on the standard deviation of the distribution is described.

Terrell, G. R.↗