quantile_conflation: Calculate the quantile for a given probabiliy under a conflated distribution

Usage

quantile_conflation(p, data, output = c("quantile", "optim"))

Arguments

p: A float with the desired probability for which the quantile is to be calculated.
data: A data frame which results from calling `conflate`.
output: One of two values, either "quantile" or "optim". The former returns only the optimised quantile value, whereas the latter returns the complete output from `optim`. Useful for checking whether optimisation converged.

Value

Either a vector of length one withe the quantile value, or a list as returned by optim.

Examples

# \donttest{
conflated = density(rnorm(1000000, 0, 1))[c("x", "y")]
quantile_conflation(0.5, conflated, output = "quantile")
#> [1] -3.549484e-05
quantile_conflation(0.5, conflated, output = "opt")
#> $par
#> [1] -3.549484e-05
#> 
#> $value
#> [1] 3.240247e-19
#> 
#> $counts
#> function gradient 
#>       NA       NA 
#> 
#> $convergence
#> [1] 0
#> 
#> $message
#> NULL
#> 
quantile_conflation(0.025, conflated, "quan")
#> [1] -1.962487
quantile_conflation(0.975, conflated, "q")
#> [1] 1.964131
# }