ex1.dag.data {abn} | R Documentation |

## Synthetic validation data set for use with abn library examples

### Description

10000 observations simulated from a DAG with 10 variables from Poisson, Bernoulli and Gaussian distributions.

### Usage

```
ex1.dag.data
```

### Format

A data frame, binary variables are factors.
The relevant formulas are given below (note these do not give parameter
estimates just the form of the relationships, like in glm(),
e.g. logit()=1+p1 means a logit link function and comprises of an
intercept term and a term involving p1).

- b1
binary, logit()=1

- p1
poisson, log()=1

- g1
gaussian, identity()=1

- b2
binary, logit()=1

- p2
poisson, log()=1+b1+p1

- b3
binary, logit()=1+b1+g1+b2

- g2
gaussian, identify()=1+p1+g1+b2

- b4
binary, logit()=1+g1+p2

- b5
binary, logit()=1+g1+g2

- g3
gaussian, identity()=1+g1+b2

### Examples

```
## The data is one realisation from the the underlying DAG:
ex1.true.dag <- matrix(data=c(
0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,
0,0,0,0,0,0,0,0,0,0,
1,1,0,0,0,0,0,0,0,0,
1,0,1,1,0,0,0,0,0,0,
0,1,1,1,0,0,0,0,0,0,
0,0,1,0,1,0,0,0,0,0,
0,0,1,0,0,0,1,0,0,0,
0,0,1,1,0,0,0,0,0,0), ncol=10, byrow=TRUE)
colnames(ex1.true.dag) <- rownames(ex1.true.dag) <-
c("b1","p1","g1","b2","p2","b3","g2","b4","b5","g3")
```

[Package

*abn* version 3.0.4

Index]