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A response burden arises from the need for
statistical information about finite populations. In
business surveys the response burden is an important
aspect since one business may fall in surveys many
times in a given time interval. This raises a
question. How to even out this burden as fairly as
possible? Poisson sampling, with Bernoulli sampling
and Bernoullis sampling and strict Poisson sampling
as special cases, has been found in the early
seventies to have good properties as regards sample
co-ordination.
A new approach for sample co-ordination, the Poisson
Mixture (PoMix) sampling is introduced in this
study. This is a sampling scheme which partly uses
Bernoulli sampling scheme and partly Strict Poisson
sampling scheme. This study also proves this
sampling scheme to be more efficient than the
traditional Poisson Sampling.
statistical information about finite populations. In
business surveys the response burden is an important
aspect since one business may fall in surveys many
times in a given time interval. This raises a
question. How to even out this burden as fairly as
possible? Poisson sampling, with Bernoulli sampling
and Bernoullis sampling and strict Poisson sampling
as special cases, has been found in the early
seventies to have good properties as regards sample
co-ordination.
A new approach for sample co-ordination, the Poisson
Mixture (PoMix) sampling is introduced in this
study. This is a sampling scheme which partly uses
Bernoulli sampling scheme and partly Strict Poisson
sampling scheme. This study also proves this
sampling scheme to be more efficient than the
traditional Poisson Sampling.