R Under development (unstable) (2023-11-12 r85514 ucrt) -- "Unsuffered Consequences"
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> require(robustlmm)
Loading required package: robustlmm
Loading required package: lme4
Loading required package: Matrix
> 
> set.seed(1)
> DyestuffWithOffset <- within(Dyestuff, {
+                            offset <- rnorm(length(Yield))
+                            Yield <- Yield + offset
+ })
> 
> testFormula <- function(formula, data) {
+     print(summary(fm <- lmer(formula, data, control=lmerControl(optimizer="bobyqa"))))
+     print(summary(rm <- rlmer(formula, data, rho.e = cPsi, rho.b = cPsi, init = lmerNoFit)))
+     ranef.fm <- ranef(fm, condVar=FALSE)
+     stopifnot(all.equal(coef(fm), coef(rm), tolerance = 1e-3, check.attributes = FALSE),
+               all.equal(fixef(fm), fixef(rm), tolerance = 1e-3, check.attributes = FALSE),
+               all.equal(ranef.fm , ranef(rm), tolerance = 1e-2, check.attributes = FALSE),
+               all.equal(fitted(fm) , fitted(rm), tolerance = 1e-3, check.attributes = FALSE),
+               all.equal(predict(fm) , predict(rm), tolerance = 1e-3, check.attributes = FALSE))
+     invisible(list(fm, rm))
+ }
> 
> testFormula(Yield ~ offset(offset) + (1 | Batch), DyestuffWithOffset)
Linear mixed model fit by REML ['lmerMod']
Formula: Yield ~ offset(offset) + (1 | Batch)
   Data: data
Control: lmerControl(optimizer = "bobyqa")

REML criterion at convergence: 319.7

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-1.4117 -0.7634  0.1418  0.7792  1.8296 

Random effects:
 Groups   Name        Variance Std.Dev.
 Batch    (Intercept) 1764     42.00   
 Residual             2451     49.51   
Number of obs: 30, groups:  Batch, 6

Fixed effects:
            Estimate Std. Error t value
(Intercept)  1527.50      19.38    78.8
Robust linear mixed model fit by DAStau 
Formula: formula 
   Data: data 

Scaled residuals: 
    Min      1Q  Median      3Q     Max 
-1.4249 -0.7476  0.1632  0.7990  1.8314 

Random effects:
 Groups   Name        Variance Std.Dev.
 Batch    (Intercept) 1764     42.00   
 Residual             2475     49.75   
Number of obs: 30, groups: Batch, 6

Fixed effects:
            Estimate Std. Error t value
(Intercept)   1527.6       19.4   78.73

Robustness weights for the residuals: 
 All 30 weights are ~= 1.

Robustness weights for the random effects: 
[1] 1 1 1 1 1 1

Rho functions used for fitting:
  Residuals:
    eff: classic 
    sig: classic 
  Random Effects, variance component 1 (Batch):
    eff: classic 
    vcp: classic 
> 
> 
> proc.time()
   user  system elapsed 
   3.03    0.25    3.28