Abstract
The efficiency of mixture distributions for sampling an alternating Poisson process (0,1 observations) is evaluated by the inverse ratio of the variance of the proportion estimate, p, to the binomial variance. The variance ratio presented by D.R.Cox (in Renewal Theory) for fixed interval sampling is generalized to accommodate a mixture of fixed interval and random sampling. The result is a sampling design tool allowing for quantifications of the effect of various spacings between observations and various mixtures. Direct application is made to the field of work sampling where the mixture model appears to be more practical than the fixed interval delay followe by random interval model previously presented by Pape.
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