Computes a confidence interval for the Poisson counts.

poiCI(x, conf.level = 0.95, type = c("exact", "daly", "byar",
  "asymptotic"), verbose = FALSE)

Arguments

x

A single number or vector that represents the number of observed successes.

conf.level

A number that indicates the level of confidence to use for constructing confidence intervals (default is 0.95).

type

A string that identifies the type of method to use for the calculations. See details.

verbose

A logical that indicates whether x should be included in the returned matrix (=TRUE) or not (=FALSE; DEFAULT).

Value

A #x2 matrix that contains the lower and upper confidence interval bounds as columns and, if verbose=TRUE x.

Details

Computes a CI for the Poisson counts using the exact, gamma distribution (daly`), Byar's (byar), or normal approximation (asymptotic) methods. This is largely a wrapper to pois.exact, pois.daly, pois.byar, and pois.approx functions documented in pois.conf.intin epitools.

See also

See pois.exact, pois.daly, pois.byar, and pois.approx (documented in pois.conf.int) in epitools for more description and references.

Examples

## Demonstrates using all types at once poiCI(12)
#> 95% LCI 95% UCI #> Exact 6.200603 20.96156 #> Daly 6.200575 20.96159 #> Byar 6.552977 20.32447 #> Asymptotic 5.210486 18.78951
## Selecting types poiCI(12,type="daly")
#> 95% LCI 95% UCI #> 6.200575 20.96159
poiCI(12,type="byar")
#> 95% LCI 95% UCI #> 6.552977 20.32447
poiCI(12,type="asymptotic")
#> 95% LCI 95% UCI #> 5.210486 18.78951
poiCI(12,type="asymptotic",verbose=TRUE)
#> x 95% LCI 95% UCI #> Asymptotic 12 5.210486 18.78951
poiCI(12,type=c("exact","daly"))
#> 95% LCI 95% UCI #> Exact 6.200603 20.96156 #> Daly 6.200575 20.96159
poiCI(12,type=c("exact","daly"),verbose=TRUE)
#> x 95% LCI 95% UCI #> Exact 12 6.200603 20.96156 #> Daly 12 6.200575 20.96159
## Demonstrates use with multiple inputs poiCI(c(7,10),type="exact")
#> 95% LCI 95% UCI #> 2.814358 14.42268 #> 4.795389 18.39036
poiCI(c(7,10),type="exact",verbose=TRUE)
#> x 95% LCI 95% UCI #> [1,] 7 2.814358 14.42268 #> [2,] 10 4.795389 18.39036