Mixed Models
library(JuliaCall)
system.time(j <- julia_setup(verbose = FALSE))
## user system elapsed
## 12.565 0.936 13.061
j$library("MixedModels")
attach("~/.julia/v0.6/MixedModels/test/dat.rda")
str(kb07)
## 'data.frame': 1790 obs. of 10 variables:
## $ G: Factor w/ 56 levels "30","31","34",..: 1 1 1 1 1 1 1 1 1 1 ...
## $ H: Factor w/ 32 levels "1","2","3","4",..: 1 2 3 4 5 6 7 8 9 10 ...
## $ Y: num 2267 3856 1567 1732 2660 ...
## $ S: num 1 -1 -1 1 1 -1 -1 1 1 -1 ...
## $ T: num -1 1 -1 1 -1 1 -1 1 -1 1 ...
## $ U: num 1 -1 -1 -1 -1 1 1 1 1 -1 ...
## $ V: num -1 -1 1 1 -1 -1 1 1 -1 -1 ...
## $ W: num 1 1 1 -1 -1 -1 -1 1 1 1 ...
## $ X: num -1 -1 1 -1 1 1 -1 1 -1 -1 ...
## $ Z: num -1 1 -1 -1 1 -1 1 1 -1 1 ...
system.time(fm1 <- j$call("fit", j$eval("LinearMixedModel"), Y ~ 1+S+T+U+V+W+X+Z + (1+S+T+U+V+W+X+Z|G) + (1+S+T+U+V+W+X+Z|H), kb07))
## user system elapsed
## 95.285 3.075 64.182
fm1
## Julia Object of type MixedModels.LinearMixedModel{Float64}.
## Linear mixed model fit by maximum likelihood
## Formula: Y ~ 1 + S + T + U + V + W + X + Z + ((1 + S + T + U + V + W + X + Z) | G) + ((1 + S + T + U + V + W + X + Z) | H)
## logLik -2 logLik AIC BIC
## -1.42931591×10⁴ 2.85863181×10⁴ 2.87483181×10⁴ 2.91930058×10⁴
##
## Variance components:
## Column Variance Std.Dev. Corr.
## G (Intercept) 90678.3925 301.128531
## S 5180.5766 71.976223 -0.43
## T 5538.3873 74.420342 -0.47 0.08
## U 7587.6112 87.106895 0.21 -0.20 0.41
## V 8834.9690 93.994516 0.20 -0.76 -0.54 -0.20
## W 1821.8560 42.683205 0.47 -0.53 -0.11 -0.44 0.29
## X 7425.1050 86.169049 -0.10 0.13 -0.05 -0.86 -0.06 0.70
## Z 3805.3075 61.687174 -0.48 0.41 -0.39 -0.09 0.18 -0.78 -0.39
## H (Intercept) 129927.0794 360.453991
## S 1854.1518 43.059863 -0.34
## T 62424.3596 249.848673 -0.68 -0.45
## U 2949.0760 54.305396 0.20 -0.03 -0.18
## V 1040.2093 32.252276 0.57 -0.76 0.02 0.01
## W 1621.4556 40.267302 0.28 -0.03 -0.27 0.44 -0.21
## X 4704.0996 68.586439 0.08 -0.24 0.21 -0.13 -0.26 0.01
## Z 4831.3038 69.507581 0.04 -0.47 0.32 -0.68 0.65 -0.68 -0.10
## Residual 399611.0928 632.147999
## Number of obs: 1790; levels of grouping factors: 56, 32
##
## Fixed-effects parameters:
## Estimate Std.Error z value P(>|z|)
## (Intercept) 2180.63 76.8294 28.3827 <1e-99
## S -66.9899 19.3321 -3.46521 0.0005
## T -333.881 47.6754 -7.00323 <1e-11
## U 78.9869 21.2351 3.71964 0.0002
## V 22.1517 20.336 1.08929 0.2760
## W -18.9244 17.5066 -1.08099 0.2797
## X 5.26198 22.4248 0.23465 0.8145
## Z -23.951 21.0288 -1.13896 0.2547