abn (version 1.3)

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).

b1

binary, logit()=1

b2

binary, logit()=1

b3

binary, logit()=1

b4

binary, logit()=1

b5

binary, logit()=1

b6

binary, logit()=1

b7

binary, logit()=1

b8

binary, logit()=1

b9

binary, logit()=1

b10

binary, logit()=1

g1

gaussian, identity()=1

g2

gaussian, identity()=1

g3

gaussian, identity()=1

g4

gaussian, identity()=1

g5

gaussian, identity()=1

g6

gaussian, identity()=1

g7

gaussian, identity()=1

g8

gaussian, identity()=1

g9

gaussian, identity()=1

g10

gaussian, identity()=1

p1

poisson, log()=1

p2

poisson, log()=1

p3

poisson, log()=1

p4

poisson, log()=1

p5

poisson, log()=1

p6

poisson, log()=1

p7

poisson, log()=1

p8

poisson, log()=1

p9

poisson, log()=1

p10

poisson, log()=1

Examples

# NOT RUN {
## This data set was 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)
                );
# }