19 Output priors (deal only)
The priors for a deal network may be output to file for inspection with the -output-priors. The deal Bayesian network model has a quite complex default prior which is based on the given network data, structure and imaginary sample size, see Boettcher and Dethlefsen (2003) for details. The bnlearn Bayesian network, which is the recommended and default Bayesian network model, has no prior to output, see Scutari and Denis (2014) for details.
The options are as follows:
| Option | Description | Default |
|---|
| -output-priors | do a task to output the priors of a network to file | |
| -output-priors-name name | label the task with a name | Task-n |
| -output-priors-network-name network | output priors for this network | previous network (or the default model given by a node for each data variable and no edges if there is no previous network) |
| -output-priors-file priors.dat | output the priors to file priors.dat | priors.dat |
The following is an example parameter file to output the priors of a network.
#input continuous data
-input-data
-input-data-file example-cts.dat
-input-data-cts
#input discrete data
-input-data
-input-data-file example-discrete.dat
-input-data-discrete
#input SNP data as discrete data
-input-data
-input-data-file example.bed
-input-data-discrete-snp
#input the example network in format 1
-input-network
-input-network-file example-network-format1.dat
-input-network-type deal
#output the priors to file
-output-priors
-output-priors-file example-priors.dat
This parameter file, paras-output-priors.txt, can be found in example.zip and can be used as follows:
./bayesnetty paras-output-priors.txt
Which should produce output that looks like something as follows:
BayesNetty: Bayesian Network software, v1.00
--------------------------------------------------
Copyright 2015-present Richard Howey, GNU General Public License, v3
Institute of Genetic Medicine, Newcastle University
Random seed: 1551957572
--------------------------------------------------
Task name: Task-1
Loading data
Continuous data file: example-cts.dat
Number of ID columns: 2
Including (all) 2 variables in analysis
Each variable has 1500 data entries
Missing value: not set
--------------------------------------------------
--------------------------------------------------
Task name: Task-2
Loading data
Discrete data file: example-discrete.dat
Number of ID columns: 2
Including the 1 and only variable in analysis
Each variable has 1500 data entries
Missing value: NA
--------------------------------------------------
--------------------------------------------------
Task name: Task-3
Loading data
SNP binary data file: example.bed
SNP data treated as discrete data
Total number of SNPs: 2
Total number of subjects: 1500
Number of ID columns: 2
Including (all) 2 variables in analysis
Each variable has 1500 data entries
--------------------------------------------------
--------------------------------------------------
Task name: Task-4
Loading network
Network file: example-network-format1.dat
Network type: deal
Total number of nodes: 5 (Discrete: 3 | Factor: 0 | Continuous: 2)
Total number of edges: 4
Network Structure: [mood][rs1][rs2][pheno|rs1:rs2][express|pheno:mood]
Imaginary sample size: 10
Total data at each node: 1495
Missing data at each node: 5
--------------------------------------------------
--------------------------------------------------
Task name: Task-5
Outputting priors
Network: Task-4
Network Structure: [mood][rs1][rs2][pheno|rs1:rs2][express|pheno:mood]
Output priors to file: example-priors.dat
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Run time: less than one second
The data is loaded, the network input and then the prior is output to a file.
