PharmCat

> > > I'm still not sure I understand what you're asking for but it does seem important and the kind of thing we'd like to support; if you have...

> ubject to semver and may break or be removed at any time) like [`asgn`](https://github.com/JuliaStats/StatsModels.jl/blob/0d0c2bbd56b183491e8c831a92168d4265e4ea68/src/modelframe.jl#L210-L215) (wraps `width` to compute the `assign` field) and [`symequal`](https://github.com/JuliaStats/StatsModels.jl/blob/0d0c2bbd56b183491e8c831a92168d4265e4ea68/src/schema.jl#L384) (which will tell you whether two...

> @kleinschmidt , I thing using `asgn` with ModelFrame is not good with this: `length(StatsModels.asgn(mf.f.rhs.terms[i]))` is any other method to do this? ``` function lcontrast(mf::ModelFrame, n::Int) terms = mf.f.rhs.terms len...

> the `ModelMatrix` struct is planned to be deprecated in the next breaking release Is it possible to include 'termsyms' and 'termvars' to public API?

This also holds using view with MvNormal distribution

> Because `one` returns the multiplicative identity, i.e., a value such that `one(x) * x == x`. Therefore, `one(5u"hr")` cannot return a value with units `hr`, because `1hr * 5hr`...

R use QR decomposition with pivoting. I suppose QR is generally using for linar models, and it recommended by https://www.stat.wisc.edu/courses/st849-bates/lectures/Orthogonal.pdf and in other software (for example you can examine SPSS...

Hello! I checked code. Ok, this line should be: ``` categorical!(df, :Per); ``` but it not changing results. All shanges from: ols = lm(@formula(LnVar ~ Seq+Per+Trt+Subj), df, **true**); allowrankdeficient::Bool=false It's...

> I can confirm that this fixes the issue - I guess this can be closed, or changed to a documentation issue on `allowrankdeficient`? Hi! Thank you very much! I...

For simmilar data I have: should values for Subject: 15 should be dropped from results? (RegressionTables.jl, not working with this results because P is NaN) ``` julia> olscmax StatsModels.TableRegressionModel{LinearModel{GLM.LmResp{Vector{Float64}}, GLM.DensePredChol{Float64,...