abn (version 3.0.1)

ex0.dag.data: Synthetic validation data set for use with abn library examples

Description

300 observations simulated from a DAG with 10 binary variables, 10 Gaussian variables and 10 poisson variables.

Usage

ex0.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, e.g. logit()=1 means a logit link function and comprises of only an intercept term).

• b1binary, logit()=1

• b2binary, logit()=1

• b3binary, logit()=1

• b4binary, logit()=1

• b5binary, logit()=1

• b6binary, logit()=1

• b7binary, logit()=1

• b8binary, logit()=1

• b9binary, logit()=1

• b10binary, logit()=1

• g1gaussian, identity()=1

• g2gaussian, identity()=1

• g3gaussian, identity()=1

• g4gaussian, identity()=1

• g5gaussian, identity()=1

• g6gaussian, identity()=1

• g7gaussian, identity()=1

• g8gaussian, identity()=1

• g9gaussian, identity()=1

• g10gaussian, identity()=1

• p1poisson, log()=1

• p2poisson, log()=1

• p3poisson, log()=1

• p4poisson, log()=1

• p5poisson, log()=1

• p6poisson, log()=1

• p7poisson, log()=1

• p8poisson, log()=1

• p9poisson, log()=1

• p10poisson, log()=1

Examples

if (FALSE) {
## The dataset was (essentially) generated using the following code:
datasize <- 300
tmp <- c(rep("y", as.integer(datasize/2)), rep("n", as.integer(datasize/2)))
set.seed(1)

ex0.dag.data <- data.frame(b1=sample(tmp, size=datasize, replace=TRUE),
                           b2=sample(tmp, size=datasize, replace=TRUE),
                           b3=sample(tmp, size=datasize, replace=TRUE),
                           b4=sample(tmp, size=datasize, replace=TRUE),
                           b5=sample(tmp, size=datasize, replace=TRUE),
                           b6=sample(tmp, size=datasize, replace=TRUE),
                           b7=sample(tmp, size=datasize, replace=TRUE),
                           b8=sample(tmp, size=datasize, replace=TRUE),
                           b9=sample(tmp, size=datasize, replace=TRUE),
                           b10=sample(tmp, size=datasize, replace=TRUE),
                           g1=rnorm(datasize, mean=0,sd=1),
                           g2=rnorm(datasize, mean=0,sd=1),
                           g3=rnorm(datasize, mean=0,sd=1),
                           g4=rnorm(datasize, mean=0,sd=1),
                           g5=rnorm(datasize, mean=0,sd=1),
                           g6=rnorm(datasize, mean=0,sd=1),
                           g7=rnorm(datasize, mean=0,sd=1),
                           g8=rnorm(datasize, mean=0,sd=1),
                           g9=rnorm(datasize, mean=0,sd=1),
                           g10=rnorm(datasize, mean=0,sd=1),
                           p1=rpois(datasize, lambda=10),
                           p2=rpois(datasize, lambda=10),
                           p3=rpois(datasize, lambda=10),
                           p4=rpois(datasize, lambda=10),
                           p5=rpois(datasize, lambda=10),
                           p6=rpois(datasize, lambda=10),
                           p7=rpois(datasize, lambda=10),
                           p8=rpois(datasize, lambda=10),
                           p9=rpois(datasize, lambda=10),
                           p10=rpois(datasize, lambda=10))
}