summary.bess.one=function(object, ...){
max.steps = object$max.steps
df = sum(object$beta!=0)
predictors = names(which(object$beta!=0))
a=rbind(predictors, object$beta[predictors])
cat("----------------------------------------------------------------------\n")
cat(" Primal-dual active algorithm with maximum iteration being", max.steps, "\n\n")
cat(" Best model with k =", df, "includes predictors:", "\n\n")
print(object$beta[predictors])
cat("\n")
if(logLik(object)[2]>=0)
cat(" log-likelihood: ", logLik(object)[2],"\n") else cat(" log-likelihood: ", logLik(object)[2],"\n")
if(deviance(object)[2]>=0)
cat(" deviance: ", deviance(object)[2],"\n") else cat(" deviance: ", deviance(object)[2],"\n")
if(object$AIC>=0)
cat(" AIC: ", object$AIC,"\n") else cat(" AIC: ", object$AIC,"\n")
if(object$BIC>=0)
cat(" BIC: ", object$BIC,"\n") else cat(" BIC: ", object$BIC,"\n")
if(object$EBIC>=0)
cat(" EBIC: ", object$EBIC,"\n") else cat(" EBIC: ", object$EBIC,"\n")
cat("----------------------------------------------------------------------\n")
}
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