restrikor() function

The restriktor() function computes the restricted estimates. The minimal requirement for this function is a fitted unconstrained model object. currently, restriktor can deal with the standard linear model (lm), the robust estimation of the linear model (rlm), and the generalized linear model (glm):

restriktor(object, constraints = NULL, se = "standard", B = 999,
           rhs = NULL, neq = 0L, mix.weights = "pmvnorm",
           mix.bootstrap = 99999L, parallel = "no", ncpus = 1L,
           cl = NULL, seed = NULL, control = NULL, verbose = FALSE,
           debug = FALSE, ...)

All available options and default settings are discussed below.

The restriktor() syntax might look as follows:

restr.ANOVA <- restriktor(fit.ANOVA, constraints = myConstraints)

For the restriktor object is a print() and a summary() function available. The print() function gives a brief overview of the restricted estimates.

print(restr.ANOVA)

Call:
conLM.lm(object = fit.ANOVA, constraints = myConstraints)

restriktor (0.1-70): restricted linear model:

Coefficients:
 GroupActive       GroupNo  GroupPassive  
      10.125        12.350        11.375  

The summary() function provides a clear summary of the restricted estimates, standard errors and p-values. In case of bootstrapped standard errors confidence intervals are computed. The summary results can be requested as follows:

summary(restr.ANOVA)

Call:
conLM.lm(object = fit.ANOVA, constraints = myConstraints)

Restriktor: restricted linear model:

Residuals:
   Min     1Q Median     3Q    Max 
-1.375 -0.850 -0.375  0.375  3.625 

Coefficients:
             Estimate Std. Error t value  Pr(>|t|)    
GroupActive  10.12500    0.61854  16.369 1.594e-10 ***
GroupNo      12.35000    0.67757  18.227 3.771e-11 ***
GroupPassive 11.37500    0.61854  18.390 3.344e-11 ***
---
Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

Residual standard error: 1.5151 on 14 degrees of freedom
Standard errors: standard 
Multiple R-squared remains 0.985 

Generalized Order-Restricted Information Criterion:
  Loglik  Penalty    Goric 
-29.5348   2.8418  64.7533 

The Generalized Order-Restrikted Information Criterion (GORIC) is for model selecting under (in)equality constraints and is demonstrated in example 6.

Explaining the restriktor arguments