AcceptAffCI {CooccurrenceAffinity} | R Documentation |

## Acceptability Interval

### Description

This function calculates the "Acceptability Interval" of Blaker for the log-odds parameter alpha in the Extended Hypergeometric distribution.

### Usage

```
AcceptAffCI(x, marg, lev, CPint)
```

### Arguments

`x` |
integer co-occurrence count that should properly fall within the closed interval [max(0,mA+mB-N), min(mA,mB)] |

`marg` |
a 3-entry integer vector (mA,mB,N) consisting of the first row and column totals and the table total for a 2x2 contingency table |

`lev` |
a confidence level, generally somewhere from 0.8 to 0.95 (default 0.95) |

`CPint` |
the exact conservative ("Clopper-Pearson-type") interval CI.CP calculated in the function AlphInts() |

### Details

This function calculates the "Acceptability Interval" based on "Acceptability Function" computed by AcceptAffin(). This interval, developed by Blaker (2000), was proved in that paper's Theorem 1 in a more general class of estimation problems to have three essential properties: it falls within the CI.CP confidence interval; it maintains the property of being conservative, i.e., of having coverage probability under the Extended Hypergeometric (mA,mB,N, alpha) distribution at least as large as the nominal level; and it is larger when the confidence level is larger.

### Value

This function returns the "Acceptability Interval" of Blaker (2000). The code is adapted from Blaker's Splus code for the case of an unknown binomial proportion.

### Author(s)

Eric Slud

### References

Blaker, H. (2000), â€śConfidence curves and improved exact confidence intervals for discrete distributions", Canadian Journal of Statistics 28, 783-798.

### Examples

```
auxCP = AlphInts(30,c(50,80,120), lev=0.9)$CI.CP
AcceptAffCI(30,c(50,80,120), 0.9, auxCP)
AlphInts(30,c(50,80,120), lev=0.9)$CI.Blaker
```

*CooccurrenceAffinity*version 1.0 Index]