Poisson Mixture Sampling in Controlling the Distribution of Response Burden in Longitudinal and Cross Section Business Surveys¶
Teikari, I. (2001). Poisson Mixture Sampling in Controlling the Distribution of Response Burden in Longitudinal and Cross Section Business Surveys.
Cited by¶
1 citation across 1 artifact.
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Domain-specific¶
- Bernoulli sampling
- For a finite frame of $N$ units under a pure common-$p$ draw, the sample size is binomial, $n_s\sim\operatorname{Binomial}(N,p)$, with expectation $Np$ and variance $Np(1-p)$.
This sourceFull Statistics Finland PDF inspected; Bernoulli membership indicators, binomial count and equal-probability relation to Poisson sampling are stated there.
- For a finite frame of $N$ units under a pure common-$p$ draw, the sample size is binomial, $n_s\sim\operatorname{Binomial}(N,p)$, with expectation $Np$ and variance $Np(1-p)$.
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