summary.surerob: Summary of surerob estimation

Description

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

Usage

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

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.

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.

Author

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

Run this code

  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)

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