Predictions from System Estimation
Returns the predicted values, their standard errors and the confidence limits of prediction.
## S3 method for class 'systemfit'
predict( object, newdata = NULL,
se.fit = FALSE, se.pred = FALSE,
interval = "none", level=0.95,
useDfSys = NULL, ... )
## S3 method for class 'systemfit.equation'
predict( object, newdata = NULL,
se.fit = FALSE, se.pred = FALSE,
interval = "none", level=0.95,
useDfSys = NULL, ... )object |
an object of class |
newdata |
An optional data frame in which to look for variables with
which to predict. If it is |
se.fit |
return the standard error of the fitted values? |
se.pred |
return the standard error of prediction? |
interval |
Type of interval calculation ("none", "confidence" or "prediction") |
level |
Tolerance/confidence level. |
useDfSys |
logical. Use the degrees of freedom of the whole system
(in place of the degrees of freedom of the single equation)
to calculate the confidence or prediction intervals.
If it not specified ( |
... |
additional optional arguments. |
The variance of the fitted values
(used to calculate the standard errors of the fitted values
and the "confidence interval") is calculated by
Var[E[y^0]-\hat{y}^0]=x^0 \; Var[b] \; {x^0}'
The variances of the predicted values
(used to calculate the standard errors of the predicted values
and the "prediction intervals") is calculated by
Var[y^0-\hat{y}^0]=\hat{σ}^2+x^0 \; Var[b] \; {x^0}'
predict.systemfit returns a dataframe that
contains for each equation the predicted values
("<eqnLable>.pred") and if requested
the standard errors of the fitted values ("<eqnLable>.se.fit"),
the standard errors of the prediction ("<eqnLable>.se.pred"),
and the lower ("<eqnLable>.lwr") and upper ("<eqnLable>.upr")
limits of the confidence or prediction interval(s).
predict.systemfit.equation returns a dataframe that
contains the predicted values ("fit") and if requested
the standard errors of the fitted values ("se.fit"),
the standard errors of the prediction ("se.pred"),
and the lower ("lwr") and upper ("upr")
limits of the confidence or prediction interval(s).
Arne Henningsen arne.henningsen@googlemail.com
Greene, W. H. (2003) Econometric Analysis, Fifth Edition, Macmillan.
Gujarati, D. N. (1995) Basic Econometrics, Third Edition, McGraw-Hill.
Kmenta, J. (1997) Elements of Econometrics, Second Edition, University of Michigan Publishing.
data( "Kmenta" ) eqDemand <- consump ~ price + income eqSupply <- consump ~ price + farmPrice + trend system <- list( demand = eqDemand, supply = eqSupply ) ## OLS estimation fitols <- systemfit( system, data=Kmenta ) ## predicted values and limits predict( fitols ) ## predicted values of the first equation predict( fitols$eq[[1]] ) ## predicted values of the second equation predict( fitols$eq[[2]] )
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