se.ratio.systemfit: Ratio of the Standard Errors

Description Usage Arguments Value Author(s) References See Also Examples

View source: R/smallMethods.R

Description

se.ratio.systemfit returns a vector of the ratios of the standard errors of the predictions for two equations.

Usage

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se.ratio.systemfit( resultsi, resultsj, eqni )

Arguments

resultsi

an object of type systemfit.

resultsj

an object of type systemfit.

eqni

index for equation to obtain the ratio of standard errors.

Value

se.ratio returns a vector of the standard errors of the ratios for the predictions between the predicted values in equation i and equation j.

Author(s)

Jeff D. Hamann [email protected]

References

Hasenauer, H; Monserud, R and T. Gregoire. (1998) Using Simultaneous Regression Techniques with Individual-Tree Growth Models. Forest Science. 44(1):87-95

See Also

systemfit and correlation.systemfit

Examples

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data( "Kmenta" )
eqDemand <- consump ~ price + income
eqSupply <- consump ~ price + farmPrice + trend
inst <- ~ income + farmPrice + trend
system <- list( demand = eqDemand, supply = eqSupply )

## perform 2SLS on each of the equations in the system
fit2sls <- systemfit( system, "2SLS", inst = inst, data = Kmenta )
fit3sls <- systemfit( system, "3SLS", inst = inst, data = Kmenta )

## print the results from the fits
print( fit2sls )
print( fit3sls )
print( "covariance of residuals used for estimation (from 2sls)" )
print( fit3sls$residCovEst )
print( "covariance of residuals" )
print( fit3sls$residCov )

## examine the improvement of 3SLS over 2SLS by computing
## the ratio of the standard errors of the estimates
improve.ratio <- se.ratio.systemfit( fit2sls, fit3sls, 2 )
print( "summary values for the ratio in the std. err. for the predictions" )
print( summary( improve.ratio ) )

systemfit documentation built on April 6, 2018, 3:08 p.m.