R: Summary of surerob estimation

summary.surerob {robustsur}

R Documentation

Summary of surerob estimation

Description

These functions create and print summary results of the estimated equation system.

Usage

## S3 method for class 'surerob'
summary(object, residCov=TRUE, equations=TRUE, ...)
## S3 method for class 'summary.surerob'
print(x, digits=max(3, getOption("digits")-1),
   residCov=x$printResidCov, equations=x$printEquations, ...)

Arguments

`object`	an object of class `surerob`.
`x`	an object of class `summary.surerob`.
`residCov`	logical. If `TRUE`, the residual correlation matrix, the residual covariance matrix, and its determinant are printed.
`equations`	logical. If `TRUE`, summary results of each equation are printed. If `FALSE`, just the coefficients are printed.
`digits`	number of digits to print.
`...`	not yet used.

Value

Applying summary on an object of class surerob returns a list of class summary.surerob. An object of class summary.surerob contains all results that belong to the whole system. This list contains one special object: eq. This is a list and contains objects of class summary.lmrob. These objects contain the results that belong to each of the estimated equations.

The objects of classes summary.surerob have the following components

`method`	estimation method.
`residuals`	residuals.
`residCovEst`	residual covariance matrix used for estimation.
`residCov`	estimated residual covariance matrix.
`residCor`	correlation matrix of the residuals.
`detResidCov`	determinant of `residCov`.
`rweights`	matrix of robust weights.
`eq`	a list containing the summary from function `summary.lmrob` and `ssr`: residual sum of squares, `eqnNo`: equation number and `eqnLabel`: equation label.
`df`	degrees of freedom, a 2-vector, where the first element is the number of coefficients and the second element is the number of observations minus the number of coefficients.
`coefficients`	a matrix with columns for the estimated coefficients, their standard errors, t-statistic and corresponding (two-sided) p-values.
`ssr_weighted`	weighted residual sum of squares.
`r.squared`	`R^2` value.
`adj.r.squared`	adjusted `R^2` value.
`coefCov`	estimated covariance matrix of the coefficients.
`printResidCov`	argument `residCov`.
`printEquations`	argument `equations`.
`control`	list of control parameters used for the estimation.
`call`	the matched call of `surerob`.

Author(s)

Claudio Agostinelli and Giovanni Saraceno

References

Giovanni Saraceno, Fatemah Alqallaf and Claudio Agostinelli (2021?) A Robust Seemingly Unrelated Regressions For Row-Wise And Cell-Wise Contamination, submitted

Examples

  library(systemfit)
  data("Kmenta")
  eqDemand <- consump~price+income
  eqSupply <- consump~price+farmPrice+trend
  system <- list(demand=eqDemand, supply=eqSupply)
     
  ## Robust estimation
  fitrob <- surerob(system, data=Kmenta)
  summary(fitrob)

[Package robustsur version 0.0-7 Index]