Metida.jl

KO | EN

gitlite — search

#javascript #python #react #typescript #llm #rust #deep-learning #windows #awesome #awesome-list #security #openai #mcp #ios

(★ 29)

Julia package for fitting mixed-effects models with flexible random/repeated covariance structure.

Metida.jl 최신버젼 다운로드

최종 버전 다운로드 (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

# Metida

This program comes with absolutely no warranty. No liability is accepted for any loss and risk to public health resulting from use of this software.

| Version | Citation | Code Coverage | Build ststus| Docs |
|---------|----------|---------------|-------------|------|
|[![version](https://juliahub.com/docs/Metida/version.svg)](https://juliahub.com/ui/Packages/Metida/asHVr)| |[![codecov](https://codecov.io/gh/PharmCat/Metida.jl/branch/master/graph/badge.svg)](https://codecov.io/gh/PharmCat/Metida.jl) |![Tier 1](https://github.com/PharmCat/Metida.jl/workflows/Tier%201/badge.svg) [![Aqua QA](https://raw.githubusercontent.com/JuliaTesting/Aqua.jl/master/badge.svg)](https://github.com/JuliaTesting/Aqua.jl) [![pkgeval](https://juliahub.com/docs/Metida/pkgeval.svg)](https://juliahub.com/ui/Packages/Metida/asHVr)| [![Latest docs](https://img.shields.io/badge/docs-latest-blue.svg)](https://pharmcat.github.io/Metida.jl/dev/) [![Stable docs](https://img.shields.io/badge/docs-stable-blue.svg)](https://pharmcat.github.io/Metida.jl/stable/)|

Metida.jl is Julia package for fitting mixed-effects models with flexible covariance structure.

Install:

```
import Pkg; Pkg.add("Metida")
```

Using:

```
using Metida, CSV, DataFrames, CategoricalArrays
df = CSV.File(joinpath(dirname(pathof(Metida)),"..","test","csv","df0.csv")) |> DataFrame
transform!(df, :subject => categorical, renamecols=false)
transform!(df, :period => categorical, renamecols=false)
transform!(df, :sequence => categorical, renamecols=false)
transform!(df, :formulation => categorical, renamecols=false)

lmm = LMM(@formula(var~sequence+period+formulation), df;
random = VarEffect(@covstr(formulation|subject), CSH),
repeated = VarEffect(@covstr(formulation|subject), DIAG),
)

fit!(lmm)

# Or you can use macro @lmmformula

lmm = LMM(@lmmformula(var~sequence+period+formulation,
    random = formulation|subject:CSH,
    repeated = formulation|subject:DIAG),
    df0)
fit!(lmm)
```

Also you can use this package with [MatidaNLopt.jl](https://github.com/PharmCat/MetidaNLopt.jl) and [MetidaCu.jl](https://github.com/PharmCat/MetidaCu.jl).

See also [MixedModels.jl](https://github.com/JuliaStats/MixedModels.jl): powerful package for mixed models.

Metida.jl

Metida.jl 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Metida.jl

Metida.jl 최신버젼 다운로드

오늘의 추천 프로젝트

Was this content helpful?

Recent Feedback

Download README