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vignettes/articles/sample-evaluation.Rmd

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```{r, include = FALSE}
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library(jfa)
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options(mc.iterations = 10000, mc.warmup = 5000)
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```
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## Introduction
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#### Approach 2: Partial pooling
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```{r, include = FALSE}
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options(mc.iterations = 10000, mc.warmup = 2000)
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```
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The partial pooling approach (`pooling = "partial"`) presumes both differences
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and similarities between strata. This enables the auditor to share information
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among the strata to minimize uncertainty in the population estimate. The
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#### Bayesian approach
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```{r, include = FALSE}
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options(mc.iterations = 15000, mc.warmup = 5000)
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```
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Bayesian inference can enhance the estimates obtained from the classical
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approach by pooling information across strata where feasible. The following
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command evaluates the `allowances` sample using a Bayesian stratified evaluation

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