Tabulation {SGB}

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 auglag).

kkt1

the first Karush-Kuhn-Tucker conditions (1=TRUE, 0=FALSE), see auglag.

kkt2

the second Karush-Kuhn-Tucker conditions (1=TRUE, 0=FALSE), see auglag.

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

regSGB, oilr, auglag.

Examples

## Overall model statistics
table.regSGB(oilr)
## 
print(coefmat(oilr),quote=FALSE)
## it is a subset of
summary(oilr)