summary.vdralogistic: Summary Method for Vertical Distributed Logistic Regression...
In vdra: Vertical Distributed Regression Analysis

Description Usage Arguments Value See Also Examples

Produces a summary of a fitted vdra logistic regression model.

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  ## S3 method for class 'vdralogistic'
  ## S3 method for class 'vdralogistic'
summary(object, ...)

`object`	a `vdralogistic` object.
`...`	futher argumetns passed to or from other methods.

Returns an object of class summary.vdralogistic. Objects of this class have a method for the function print. The following components must be included in summary.vdralogistic object.

`failed`	logical value. If `FALSE`, then there was an error processing the data. if `TRUE`, there were no errors.
`converged`	logical value. If `TRUE`, the regression converged. If `FALSE`, it did not.
`party`	a vector which indicates the party from which each covariate came.
`coefficients`	the vector of coefficients. If the model is over-determined, there will be missing values in the vector corresponding to the redudant columns model matrix.
`secoef`	the vector of the standard error of the coefficients.
`tvals`	the t-values of the coefficietns.
`pvals`	the p-values of the coefficients.
`nulldev`	the null deviance of the fit.
`nulldev_df`	the degrees of freedom for the null deviance.
`resdev`	the residual deviance of the fit.
`resdev_df`	the degrees of freedome for the residual deviance.
`aic`	the AIC of the fit.
`bic`	the BIC of the fit.
`iter`	the number of iterations of the cox algorithm before convergence.