encodedata: encodedata

In NeuralEstimators: Likelihood-Free Parameter Estimation using Neural Networks

encodedata

Description

for data Z with missing (NA) entries, returns an augmented data set (U, W) where W encodes the missingness pattern as an indicator vector and U is the original data Z with missing entries replaced by a fixed constant c.

The indicator vector W is stored in the second-to-last dimension of Z, which should be singleton. If the second-to-last dimension is not singleton, then two singleton dimensions will be added to the array, and W will be stored in the new second-to-last dimension.

Usage

encodedata(Z, c = 0)

Arguments

Z	data containing NA entries
c	fixed constant with which to replace NA entries

Value

Augmented data set (U, W). If Z is provided as a list, the return type will be a JuliaProxy object; these objects can be indexed in the usual manner (e.g., using [[), or converted to an R object using juliaGet() (note however that juliaGet() can be slow for large data sets).

Examples

## Not run: 
library("NeuralEstimators")
Z <- matrix(c(1, 2, NA, NA, 5, 6, 7, NA, 9), nrow = 3)
encodedata(Z)
encodedata(list(Z, Z))
## End(Not run)

NeuralEstimators documentation built on Nov. 3, 2024, 9:07 a.m.