Sampling Random Polygons.

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Abstract:

Every realization of a Poisson line process is a set of lines which subdivides the plane into a population of nonoverlapping convex polygons. To explore the unknown statistical features of this population, an alternative stochastic construction of random polygons is developed. This construction, which is based on an alternating sequence of random angles and side lengths, provides a fast simulation method for obtaining a random sample from the polygon population. For the isotropic case, this construction is used to obtain a random sample of 2,500,000 polygons, providing the most precise estimates to date of some of the unknown distributional characteristics. Keywords geometric probability.

Author(s):
George, Edward I.
Author Organization(s):
STANFORD UNIV CA DEPT OF STATISTICS
Descriptive Note:
Technical rept.,
Pagination:
0028

Security Markings

DOCUMENT & CONTEXTUAL SUMMARY

Distribution:
Approved For Public Release

RECORD

Collection: TR
Identifying Numbers
Report Number(s):
TR-385
Contract/Grant Number(s):
N00014-86-K-0156
 Subject Terms
Joint Capability Areas:
JCA_1.4.1_Force Health Protection; JCA_1.4_Force Support
Communities of Interest:
Air Platforms
Descriptor(s):
*MONTE CARLO METHOD, *POLYGONS, *POISSON DENSITY FUNCTIONS, ANGLES, STOCHASTIC PROCESSES, PROBABILITY, MOMENTS, POPULATION, SEQUENCES, ESTIMATES, LENGTH, ISOTROPISM, PRECISION, SAMPLING, GEOMETRY, SIDES
Field(s)/Group(s):
Statistics and Probability
Keyword(s):
*Geometric probability, Convex polygons, WUNR042267
Report Date:
1987 Dec 29