Description Usage Arguments Details Value Author(s) Examples
Specifies the control parameters for the search algorithms (i.e. either simulated annealing or MCMC) and the logic tree considered when fitting a trio logic regression model.
1 2 3 
start 
a numeric value specifying the upper temperature (on log10 scale) used as start temperature in simulated annealing.
Must be larger than 
end 
a numeric value specifying the lowest temperature (on log10 scale) used in simulated annealing. Must be smaller than

iter 
the number of iterations used in the (stochastic) search for the best trio logic regression model, i.e. either in simulated
annealing (if the argument 
earlyout 
a nonnegative integer providing an option to end the search before all 
update 
the number of iterations in simulated annealing or MCMC after which statistics for the current trio logic regression model are displayed. This argument allows to evaluate the progress in the search for the best trio logic regression model. By default, no updates are shown. 
treesize 
a positive integer specifying the maximum number of leaves allowed in the logic tree of a trio logic regression model. 
opers 
either 1, 2, or 3 specifying if both the AND and the OR operator ( 
minmass 
a nonnegative integer specifying the number of cases and pseudocontrols for which the logic expression (i.e. the logic tree)
needs to be 1 or for which the logic expression needs to be 0 to be considered as a logic tree in the trio logic regression model.
By default, 
nburn 
number of initial iterations in MCMC considered as burnin MC trio logic regression, and therefore, ignored when computing the summaries. 
hyperpars 
a numeric value specifying the hyperparameter for the prior on the model size when performing a MC trio logic regression.
More exactly, 
output 
a value specifying which statistics are returned in an MCMC trio logic regression analysis. If 
More details on the different control parameters and their specification can be found on the help pages of the functions
logreg.anneal.control
, logreg.tree.control
, and logreg.mc.control
for the different
types of control parameters available in the R
package LogicReg
for a standard logic regressions.
A list containing all required control parameters.
Holger Schwender, holger.schwender@udo.edu
1 2 3 4 5 6 7 
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.