Tabulation {SGB} | R Documentation |
Tabulation of overall SGB regression results with AIC and matrix view of regression coefficients
Description
table.regSGB: Value of the log-likelihood, number of parameters, AIC criterion, optimality tests and iterations counts.
coefmat: regression coefficients in matrix form with significance level.
Usage
table.regSGB(object)
coefmat(object,digits=3)
Arguments
object |
an object of class regSGB |
digits |
number of decimal places for the coefficients |
Value
table.regSGB
: Data frame with one column, with the overall statistics results.
value |
the maximum log-likelihood |
n.par |
the number of parameters |
n.par.fixed |
the number of fixed parameters |
AIC |
the AIC criterion |
Rsquare |
total variance of estimated over total variance of observed compositions |
convergence |
the convergence code (0: converged, others, see |
kkt1 |
the first Karush-Kuhn-Tucker conditions (1=TRUE, 0=FALSE), see |
kkt2 |
the second Karush-Kuhn-Tucker conditions (1=TRUE, 0=FALSE), see |
counts.function |
number of times the log-likelihood was evaluated. |
counts.gradient |
number of times the gradient was evaluated. |
coefmat
: character matrix with the regression coefficients arranged in columns, one for each log-ratio transform. Each ceofficient is followed by the significance level.
See Also
Examples
## Overall model statistics
table.regSGB(oilr)
##
print(coefmat(oilr),quote=FALSE)
## it is a subset of
summary(oilr)