summary.opsr {OPSR} | R Documentation |
Summarizing OPSR Model Fits
Description
Follows the convention that opsr
does the bare minimum model fitting and
inference is performed in summary
.
Usage
## S3 method for class 'opsr'
summary(object, rob = TRUE, ...)
Arguments
object |
an object of class "opsr" .
|
rob |
if TRUE , the sandwich::sandwich covariance matrix extimator is used.
|
... |
further arguments passed to or from other methods.
|
Value
An object of class "summary.opsr"
.
In particular the elements GOF
, GOFcomponents
and wald
require further
explanation:
GOF |
Contains the conventional goodness of fit indicators for the full
model. LL2step is the log-likelihood of the Heckman two-step solution (if
the default starting values were used). LLfinal is the log-likelihood at
final convergence and AIC , BIC the corresponding information critereon.
|
GOFcomponents |
Contains the goodness of fit for the model components.
LLprobit is the log-likelihood (LL) contribution of the ordered probit model.
LLprobitEl the LL of the "equally likely" and LLprobitMs the LL of the
"market share" model. With these three metrics the pseudo R2 is computed and
returned as pseudoR2el and pseudoR2ms . R2 reports the usual coefficient
of determination (for the continuous outcomes jointly and for each regime
separately).
|
wald |
Contains the results of two Wald-tests as conducted with help
of car::linearHypothesis . The two H0 hypothesis are 1. All coefficients
of the explanatory variables are 0 and 2. The rho parameters (capturing error
correlation) are zero.
|
[Package
OPSR version 1.0.0
Index]