View source: R/summary.systemfit.R
| summary.systemfit | R Documentation |
These functions create and print summary results of the estimated equation system.
## S3 method for class 'systemfit'
summary( object, useDfSys = NULL,
residCov = TRUE, equations = TRUE, ... )
## S3 method for class 'systemfit.equation'
summary( object, useDfSys = NULL, ... )
## S3 method for class 'summary.systemfit'
print( x,
digits = max( 3, getOption("digits") - 1 ),
residCov = x$printResidCov, equations = x$printEquations, ... )
## S3 method for class 'summary.systemfit.equation'
print( x,
digits = max( 3, getOption("digits") - 1 ), ... )
object |
an object of class |
x |
an object of class |
useDfSys |
logical. Use the degrees of freedom of the whole system
(in place of the degrees of freedom of the single equation)
to calculate prob values for the t-test of individual coefficients.
If it not specified ( |
digits |
number of digits to print. |
residCov |
logical. If |
equations |
logical. If |
... |
not used by user. |
Applying summary on an object of class systemfit
returns a list of class summary.systemfit.
Applying summary on an object of class
systemfit.equation
returns a list of class
summary.systemfit.equation.
An object of class summary.systemfit
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.systemfit.equation.
These objects contain the results that belong to each of the eatimated equations.
The objects of classes summary.systemfit and
summary.systemfit.equation
have the following components
(elements that are marked with a * are available only in objects of
class summary.systemfit;
elements that are marked with a + are available only in objects of
class summary.systemfit.equation):
method |
estimation method. |
residuals |
residuals. |
coefficients |
a matrix with columns for the estimated coefficients, their standard errors, t-statistic and corresponding (two-sided) p-values. |
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. |
coefCov |
estimated covariance matrix of the coefficients. |
call* |
the matched call of |
ols.r.squared* |
OLS |
mcelroy.r.squared* |
McElroy's |
iter* |
number of iteration steps (only if the estimation is iterated). |
control* |
list of control parameters used for the estimation. |
residCov* |
estimated residual covariance matrix. |
residCovEst* |
residual covariance matrix used for estimation (only SUR and 3SLS). |
residCor* |
correlation matrix of the residuals. |
detResidCov* |
determinant of |
eqnLabel+ |
equation label. |
eqnNo+ |
equation number. |
terms+ |
the 'terms' object used for the respective equation. |
r.squared+ |
|
adj.r.squared+ |
adjusted |
sigma+ |
estimated standard error of the residuals of the respective equation. |
ssr+ |
sum of squared residuals of the respective equation. |
printResidCov* |
argument |
printEquations* |
argument |
Jeff D. Hamann jeff.hamann@forestinformatics.com,
Arne Henningsen arne.henningsen@googlemail.com
systemfit, print.systemfit
data( "Kmenta" )
eqDemand <- consump ~ price + income
eqSupply <- consump ~ price + farmPrice + trend
inst <- ~ income + farmPrice + trend
system <- list( demand = eqDemand, supply = eqSupply )
## perform OLS on each of the equations in the system
fitols <- systemfit( system, data = Kmenta )
## results of the system
summary( fitols )
## short results of the system
summary( fitols, residCov = FALSE, equations = FALSE )
## results of the first equation
summary( fitols$eq[[1]] )
## results of the second equation
summary( fitols$eq[[2]] )
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