# rconst: Constant (Degenerate) Distribution (Returns its Own Argument... In osofr/simcausal: Simulating Longitudinal Data with Causal Inference Applications

## Description

Wrapper for constant value (degenerate) distribution.

## Usage

 `1` ```rconst(n, const) ```

## Arguments

 `n` Sample size. `const` Either a vector with one constant value (replicated `n` times) or a vector of length `n` or a matrix with `n` rows (for a multivariate node).

## Value

A vector of constants of length `n`.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16``` ```#--------------------------------------------------------------------------------------- # Specifying and simulating from a DAG with 1 Bernoulli and 2 constant nodes #--------------------------------------------------------------------------------------- D <- DAG.empty() D <- D + node("W1", distr = "rbern", prob = 0.45) D <- D + node("W2", distr = "rconst", const = 1) D <- D + node("W3", distr = "rconst", const = ifelse(W1 == 1, 5, 10)) # TWO equivalent ways of creating a multivariate node (just repeating W1 and W2): create_mat <- function(W1, W2) cbind(W1, W2) vecfun.add("create_mat") D <- D + node(c("W1.copy1", "W2.copy1"), distr = "rconst", const = c(W1, W2)) D <- D + node(c("W1.copy2", "W2.copy2"), distr = "rconst", const = create_mat(W1, W2)) Dset <- set.DAG(D) sim(Dset, n=10, rndseed=1) ```

osofr/simcausal documentation built on Jan. 6, 2019, 3:05 a.m.