Missing distribution

A placeholder distribution for handling missing values in a vector of distributions.

dist_missing(length = 1)

Arguments

length

The number of missing distributions

Details

We recommend reading this documentation on pkgdown which renders math nicely. https://pkg.mitchelloharawild.com/distributional/reference/dist_missing.html

The missing distribution represents the absence of distributional information. It is used as a placeholder when distribution values are not available or not applicable, similar to how NA is used for missing scalar values.

Support: Undefined

Mean: \(\text{NA}\)

Variance: \(\text{NA}\)

Skewness: \(\text{NA}\)

Kurtosis: \(\text{NA}\)

Probability density function (p.d.f): Undefined

$$ f(x) = \text{NA} $$

Cumulative distribution function (c.d.f): Undefined

$$ F(t) = \text{NA} $$

Quantile function: Undefined

$$ Q(p) = \text{NA} $$

Moment generating function (m.g.f): Undefined

$$ E(e^{tX}) = \text{NA} $$

All statistical operations on missing distributions return NA values of appropriate length, propagating the missingness through calculations.

See also

base::NA

Examples

dist <- dist_missing(3L)

dist
#> <distribution[3]>
#> [1] NA NA NA
mean(dist)
#> [1] NA NA NA
variance(dist)
#> [1] NA NA NA

generate(dist, 10)
#> [[1]]
#>  [1] NA NA NA NA NA NA NA NA NA NA
#> 
#> [[2]]
#>  [1] NA NA NA NA NA NA NA NA NA NA
#> 
#> [[3]]
#>  [1] NA NA NA NA NA NA NA NA NA NA
#> 

density(dist, 2)
#> [1] NA NA NA
density(dist, 2, log = TRUE)
#> [1] NA NA NA

cdf(dist, 4)
#> [1] NA NA NA

quantile(dist, 0.7)
#> [1] NA NA NA