Computes the shortest credible interval of the output of the MCMC algorithm for a single parameter.
Usage
credible(object, ...)
# S4 method for numeric
credible(object, level = 0.95, CE = TRUE)
# S4 method for MCMC
credible(object, level = 0.95, simplify = TRUE)
Arguments
- object
A
numeric
vector or anMCMC
object containing the output of the MCMC algorithm for the parameter.- ...
Currently not used.
- level
A length-one
numeric
vector giving the confidence level.- CE
A
logical
scalar: are the data expressed in BC/AD years?- simplify
A
logical
scalar: should the results should be simplified?
Value
If simplify
is TRUE
(the default), returns a data.frame
giving the
lower and upper boundaries of the credible interval and associated
probabilities. Else, returns a list
of numeric
Details
A \((100 \times level)\) % credible interval is an interval that keeps \(N \times (1 - level)\) elements of the sample outside the interval.
The \((100 \times level)\) % credible interval is the shortest of all those intervals.
For instance, the 95% credible interval is the central portion of the posterior distribution that contains 95% of the values.
See also
Other statistics:
hpdi()
,
sensitivity()
,
summary()
Examples
## Coerce to MCMC
eve <- as_events(events, calendar = "CE", iteration = 1)
eve <- eve[1:10000, ]
## CE
credible(eve, level = 0.95) # Credible interval
#> name lower upper p
#> 1 E1 -1045.210 -202.337 0.95
#> 2 E2 -1979.810 -1613.590 0.95
#> 3 E3 -809.057 -459.090 0.95
#> 4 E4 -1400.040 -1064.290 0.95
hpdi(eve, level = 0.68) # HPD interval
#> name lower upper p
#> 1 E1 -1009.3026 -774.1160 0.35
#> 2 E1 -490.0595 -257.9273 0.33
#> 3 E2 -1891.7506 -1690.3908 0.68
#> 4 E3 -757.2008 -604.5292 0.68
#> 5 E4 -1311.7275 -1149.4158 0.68
## BP
eve_BP <- CE_to_BP(eve)
credible(eve_BP, level = 0.95) # Credible interval
#> name lower upper p
#> 1 E1 2994.210 2151.337 0.95
#> 2 E2 3928.810 3562.590 0.95
#> 3 E3 2758.057 2408.090 0.95
#> 4 E4 3349.040 3013.290 0.95
hpdi(eve_BP, level = 0.95) # HPD interval
#> name lower upper p
#> 1 E1 3010.227 2142.786 0.95
#> 2 E2 3929.877 3558.517 0.95
#> 3 E3 2754.053 2400.858 0.95
#> 4 E4 3355.409 3015.006 0.95