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Fixed–Random Mixture Method for Work Sampling

Pen‐Yuan Liao, Elinor S. Pape

Open publisher page 4 citations

Abstract

This paper presents an approach to work sampling involving a mixture of fixed and random sampling. Fixed-interval sampling is more efficient in terms of providing more precise information for the same number of observations. Random sampling avoids the possibilities of sampling times being anticipated and the sampling schedule coinciding with some rhythm in the sampled process. Using a mixture of fixed and random sampling provides a smooth transition from fixed to random sampling and allows the practitioner to select a mixture level appropriate for his or her purposes. The efficiency of the mixture sampling method is analyzed by using an alternating Poisson process model for the sampled process. The mixture sampling method eliminates the observation-free period after every observation that was provided by the previously proposed delayed-sampling method. Although the mixture sampling method is slightly less efficient than the delayed-sampling method, its advantage is clear when anticipation of observation times is a concern, and it is always more efficient than random sampling.

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What this paper is about

This paper presents an approach to work sampling involving a mixture of fixed and random sampling. Fixed-interval sampling is more efficient in terms of providing more precise information for the same number of observations. Random sampling avoids the possibilities of sampling times being anticipated and the sampling schedule coinciding with some rhythm in the sampled process. Using a mixture of fixed and random sampling provides a smooth transition from fixed to random sampling and allows the practitioner to select a mixture level appropriate for his or her purposes. The efficiency of the mixture sampling method is analyzed by using an alternating Poisson process model for the sampled process. The mixture sampling method eliminates the observation-free period after every observation that was provided by the previously proposed delayed-sampling method. Although the mixture sampling method is slightly less efficient than the delayed-sampling method, its advantage is clear when anticipation of observation times is a concern, and it is always more efficient than random sampling.

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OpenAlex reports 4 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

This paper presents an approach to work sampling involving a mixture of fixed and random sampling. Fixed-interval sampling is more efficient in terms of providing more precise information for the same number of observations. Random sampling avoids the possibilities of sampling times being anticipated and the sampling schedule coinciding with some rhythm in the sampled process. Using a mixture of fixed and random sampling provides a smooth transition from fixed to random sampling and allows the practitioner to select a mixture level appropriate for his or her purposes. The efficiency of the mixture sampling method is analyzed by using an alternating Poisson process model for the sampled process. The mixture sampling method eliminates the observation-free period after every observation that was provided by the previously proposed delayed-sampling method. Although the mixture sampling method is slightly less efficient than the delayed-sampling method, its advantage is clear when anticipation of observation times is a concern, and it is always more efficient than random sampling.

Key concepts: Slice sampling, Sampling (signal processing), Poisson sampling, Stratified sampling, Mathematics, Statistics, Systematic sampling, Importance sampling

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