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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