
Accession Number : AD0653877
Title : RECONSTRUCTING PATTERNS FROM SAMPLE DATA.
Descriptive Note : Technical rept.,
Corporate Author : STANFORD UNIV CALIF DEPT OF STATISTICS
Personal Author(s) : Switzer,Paul
Report Date : 23 MAY 1967
Pagination or Media Count : 36
Abstract : A Euclidean region is partitioned in an unknown way into a known number of subregions. For a discrete set of points in the region we may observe into which subregion they each fall. The problem is to obtain an estimated reconstruction of the partition based on the observations. Section 1 outlines a probabilistic approach to the problem and defines criteria of goodness for an estimated reconstruction. Section 2 evaluates the performance of nearestpoint rules. Section 3 examines the effect of samplesize and compares several arrangements of the data points. Section 4 proposes a modification of nearestpoint procedures having a certain optimality property. Section 5 is more or less independent of the earlier sections; it explores several probabilistic partitioning models. (Author)
Descriptors : (*SAMPLING, MATHEMATICAL MODELS), RANDOM VARIABLES, MATHEMATICS, THEOREMS, PROBABILITY, PATTERN RECOGNITION, STATISTICAL ANALYSIS
Subject Categories : Statistics and Probability
Distribution Statement : APPROVED FOR PUBLIC RELEASE