Computes a confidence interval for the Poisson counts.
Usage
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.
The pois.daly
function gives essentially identical answers to the pois.exact
function except when x=0. When x=0, for the upper confidence limit pois.exact
returns 3.689 and pois.daly
returns 2.996.
Author
Derek H. Ogle, DerekOgle51@gmail.com, though this is largely based on pois.exact
, pois.daly
, pois.byar
, and pois.approx
from the old epitools package.
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