In this example, I want to estimate the uncertainty around the beta value for each `Cut & Clarity`

pair. Iโm not sure how to interpret the `allpars`

data. Is it producing a single sigma shared across all values of `Cut & Clarity`

? Do I need to `simulate`

in order to get what I want? I am not trying to get *prediction error*, I just want the uncertainty around the expected value at each point.

```
using RDatasets, MixedModels, DataFrames
d = dataset("ggplot2", "diamonds")
form = @formula(Price ~ (1|Cut & Clarity))
modelfit = fit(LinearMixedModel, form, d)
pb = parametricbootstrap(Random.GLOBAL_RNG, 1000, modelfit)
DataFrame(pb.allpars)
#= julia> DataFrame(pb.allpars)
3000ร5 DataFrame
Row โ iter type group names value
โ Int64 String String? String? Float64
โโโโโโโผโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโโ
1 โ 1 ฮฒ missing (Intercept) 4054.44
2 โ 1 ฯ Cut & Clarity (Intercept) 831.115
3 โ 1 ฯ residual missing 3907.46
4 โ 2 ฮฒ missing (Intercept) 3925.81
5 โ 2 ฯ Cut & Clarity (Intercept) 726.458
6 โ 2 ฯ residual missing 3908.1
7 โ 3 ฮฒ missing (Intercept) 3941.74
8 โ 3 ฯ Cut & Clarity (Intercept) 621.993
9 โ 3 ฯ residual missing 3918.18
10 โ 4 ฮฒ missing (Intercept) 3987.62
11 โ 4 ฯ Cut & Clarity (Intercept) 811.536
12 โ 4 ฯ residual missing 3929.52
13 โ 5 ฮฒ missing (Intercept) 3818.16
14 โ 5 ฯ Cut & Clarity (Intercept) 609.15
15 โ 5 ฯ residual missing 3883.62
16 โ 6 ฮฒ missing (Intercept) 3786.48
17 โ 6 ฯ Cut & Clarity (Intercept) 850.474
โฎ โ โฎ โฎ โฎ โฎ โฎ
2985 โ 995 ฯ residual missing 3911.85
2986 โ 996 ฮฒ missing (Intercept) 3802.83
2987 โ 996 ฯ Cut & Clarity (Intercept) 720.439
2988 โ 996 ฯ residual missing 3898.91
2989 โ 997 ฮฒ missing (Intercept) 3782.61
2990 โ 997 ฯ Cut & Clarity (Intercept) 734.746
2991 โ 997 ฯ residual missing 3899.4
2992 โ 998 ฮฒ missing (Intercept) 3692.06
2993 โ 998 ฯ Cut & Clarity (Intercept) 677.055
2994 โ 998 ฯ residual missing 3916.26
2995 โ 999 ฮฒ missing (Intercept) 3856.67
2996 โ 999 ฯ Cut & Clarity (Intercept) 810.09
2997 โ 999 ฯ residual missing 3912.06
2998 โ 1000 ฮฒ missing (Intercept) 3725.55
2999 โ 1000 ฯ Cut & Clarity (Intercept) 743.319
3000 โ 1000 ฯ residual missing 3906.36
2966 rows omitted =#
```