abn (version 1.0)

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)
#                 );
# ## End(Not run)