inverse_pmf: Inverse Probability Mass Function

In leonawicz/rvtable: Random Variable Data Tables

Description

Compute the probability mass function for a specified categorical variable conditional on values of the primary random variable.

Usage

inverse_pmf(x, values, id, sample.args)

Arguments

x	an rvtable.
values	range of values of the continuous random variable in the rvtable.
id	the categorical variable for which to compute the pmf given values.
sample.args	optional arguments used when sampling.

Details

This function computes the pmf of a categorical variable, providing probabilities corresponding to the levels of the variable, conditional on values of the primary random variable in the rvtable. When the primary random variable is continuous, 'values' must be a length-2 vector giving a valid range. When discrete, 'values' can be a range or a single discrete value. If conditioning on a value or range of values restricts the conditional support for 'id' to one where 'id' has probability zero everywhere, a warning will be thrown and the returned rvtable will have zero rows.

Value

an rvtable.

Examples

library(dplyr)
x <- data.frame(
  id1=rep(LETTERS[1:5], each=4),
  id2=factor(c("low", "high")),
  id3=rep(1:2, each=2),
  Val=rep(1:10, each=20), Prob=rep(sqrt(1:10), each=20)) %>% rvtable
y1 <- inverse_pmf(x, c(5, 8), "id1", sample.args=list(n=5))
y1
x <- filter(x, id2=="low" & id3==1) %>% select(-id2, -id3) %>% rvtable
y2 <- inverse_pmf(x, c(5,8), "id1", sample.args=list(n=5))
y2

leonawicz/rvtable documentation built on May 21, 2019, 5:09 a.m.