using MixedModels,RDatasets   # load packages
ds = dataset("lme4","Dyestuff")

m1 = fit(lmm(Yield ~ 1 + (1|Batch),ds))

@time fit(lmm(Yield ~ 1 + (1|Batch), ds),true);

MixedModels.hasgrad(m1)

m1.λ

fixef(m1)

ranef(m1)

deviance(m1)

ds2 = dataset("lme4","Dyestuff2");
@time m2 = fit(lmm(Yield ~ 1 + (1|Batch), ds2),true)

slp = dataset("lme4","sleepstudy");
m3 = fit(lmm(Reaction ~ 1+Days + (1+Days|Subject),slp),true)

m3.λ

MixedModels.hasgrad(m3)

m4 = fit(lmm(Reaction ~ 1+Days + (1|Subject) + (0+Days|Subject), slp),true)

@time fit(lmm(Reaction ~ 1+Days + (1|Subject) + (0+Days|Subject), slp));

MixedModels.hasgrad(m4)

m4.λ

pen = dataset("lme4","Penicillin");
m5 = fit(lmm(Diameter ~ 1 + (1|Plate) + (1|Sample),pen),true)

@time fit(lmm(Diameter ~ 1 + (1|Plate) + (1|Sample),pen));

MixedModels.hasgrad(m5)

m5.λ

psts = dataset("lme4","Pastes");
m6 = fit(lmm(Strength ~ 1 + (1|Sample) + (1|Batch),psts),true)

@time fit(lmm(Strength ~ 1 + (1|Sample) + (1|Batch),psts));

typeof(m6)

MixedModels.hasgrad(m6)

inst = dataset("lme4","InstEval");
m7 = fit(lmm(Y ~ Dept*Service + (1|S) + (1|D), inst))

@time fit(lmm(Y ~ Dept*Service + (1|S) + (1|D), inst));

typeof(m7)

chem = dataset("mlmRev","Chem97");
@time m8 = fit(lmm(Score ~ 1+GCSECnt+Gender+Age + (1|School) + (1|Lea),chem))

bs10 = MixedModels.rdata("bs10");
names(bs10)

@time m9 = fit(lmm(dif ~ 1+S+F+SF + (1+S+F+SF|SubjID) + (1+S+F+SF|ItemID), bs10))

m9.λ

kb07 = MixedModels.rdata("kb07")
names(kb07)'

@time m10 = fit(lmm(RTtrunc ~ 1+S+P+C+SP+SC+PC+SPC + (1+S+P+C+SP+SC+PC+SPC|SubjID) + (1+S+P+C+SP+SC+PC+SPC|ItemID), kb07))

m10.λ