swap to JuliaNotebookRunner backend

.gitignore

@@ -22,6 +22,7 @@ docs/site/
 # committed for packages, but should be committed for applications that require a static
 # environment.
 Manifest.toml
+Manifest-v1.*.toml
 
 /.quarto/
 .CondaPkg/

AoGPlots.qmd

@@ -1,5 +1,8 @@
 ---
 title: "Creating multi-panel plots"
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 This notebook shows creating a multi-panel plot similar to Figure 2 of @Fuehner2021.

README.md

@@ -4,24 +4,15 @@ SMLP2024: Advanced methods in frequentist statistics with Julia
 
 The rendered website version of the course materials is available [here](https://repsychling.github.io/SMLP2024/).
 
-This repository uses [Quarto](https://quarto.org). To be able to render all the pages, you will need an appropriate Jupyter kernel installed and the local environment instantiated.
+This repository uses [Quarto](https://quarto.org) with the Julia code execution supplied by [QuartoNotebookRunner.jl](https://github.com/PumasAI/QuartoNotebookRunner.jl/), which requires Quarto 1.5+.
+
+As of early May 2024, Quarto 1.5 is only available as a preview release, which you'll need to [download from GitHub](https://github.com/quarto-dev/quarto-cli/releases). Under each release's "Assets", you can find platform-specific installers.
 
 ```sh
-~/SMLP2024$ julia
+~/EmbraceUncertainty$ julia
 
 julia> using Pkg
 
-julia> Pkg.add("IJulia")
-    Updating registry at `~/.julia/registries/General.toml`
-   Resolving package versions...
-< lots of output >
-
-julia> using IJulia
-
-julia> installkernel("julia", "--threads=auto", "--project=@.")
-[ Info: Installing julia kernelspec in ~/.local/share/jupyter/kernels/julia-1.9
-"~/.local/share/jupyter/kernels/julia-1.9"
-
 julia> Pkg.activate(".")
   Activating project at `~/SMLP2024`
 
@@ -30,8 +21,7 @@ julia> Pkg.instantiate()
 
 julia> exit()
 
-~/SMLP2024$ quarto preview
+~/EmbraceUncertainty$ quarto preview
 
 < lots of output >
-
 ```

_quarto.yml

@@ -1,3 +1,13 @@
+date: today
+date-format: iso
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
+execute:
+  cache: true
+  freeze: auto
+number-sections: true
+
 project:
   type: website
   title: "SMLP2024"
@@ -29,14 +39,6 @@ project:
   - sleepstudy_speed.qmd
   - useful_packages.qmd
 
-date: today
-date-format: iso
-jupyter: julia-1.9
-execute:
-  cache: true
-  freeze: auto
-number-sections: true
-
 # editor_options:
 #   chunk_output_type: console
 filters:

arrow.qmd

@@ -1,6 +1,8 @@
 ---
 title: "Saving data with Arrow"
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 # The Arrow storage format

bootstrap.qmd

@@ -1,6 +1,8 @@
 ---
 title: "Parametric bootstrap for mixed-effects models"
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 The speed of MixedModels.jl relative to its predecessors makes the parametric bootstrap much more computationally tractable.

check_emotikon_transform.qmd

@@ -1,5 +1,8 @@
 ---
 title: Transformed and original metrics in Emotikon
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 In @Fuehner2021 the original metric of two tasks (Star, S20) is time, but they were transformed to speed scores in the publication prior to computing z-scores.

contrasts_fggk21.qmd

@@ -1,6 +1,8 @@
 ---
 title: "Mixed Models Tutorial: Contrast Coding"
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 author: "Reinhold Kliegl"
 ---
 

contrasts_kwdyz11.qmd

@@ -1,6 +1,8 @@
 ---
 title: Contrast Coding of Visual Attention Effects
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 ```{julia}

fggk21.qmd

@@ -1,6 +1,8 @@
 ---
 title: Basics with Emotikon Project
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 This script uses a subset of data reported in @Fuehner2021.

glmm.qmd

@@ -1,6 +1,8 @@
 ---
 title: "Generalized linear mixed models"
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 Load the packages to be used

index.qmd

@@ -2,6 +2,9 @@
 title: "Seventh Summer School on Statistical Methods for Linguistics and Psychology"
 subtitle: "Advanced methods in frequentist statistics with Julia"
 author: "Phillip Alday, Reinhold Kliegl and Douglas Bates"
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 This site provides materials for the **Advanced frequentist methods** stream of the [Summer School on Statistical Methods](https://vasishth.github.io/smlp2024/) to be held at the University of Potsdam, 11-15 September, 2024.

kb07.qmd

@@ -1,6 +1,8 @@
 ---
 title: "Bootstrapping a fitted model"
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 Begin by loading the packages to be used.

kkl15.qmd

@@ -1,6 +1,8 @@
 ---
 title: 'RePsychLing Kliegl, Kuschela, & Laubrock (2015)- Reduction of Model Complexity'
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 # Background

kwdyz11.qmd

@@ -1,6 +1,8 @@
 ---
 title: "RePsychLing Kliegl et al. (2011)"
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 author: "Reinhold Kliegl"
 ---
 

largescaledesigned.qmd

@@ -1,5 +1,7 @@
 ---
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 # A large-scale designed experiment {#sec-largescaledesigned}

mrk17.qmd

@@ -1,6 +1,8 @@
 ---
 title: "RePsychLing Masson, Rabe, & Kliegl, 2017) with Julia: Specification and selection"
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 # Setup

partial_within.qmd

@@ -1,6 +1,8 @@
 ---
 title: "Partially-within subjects designs"
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 Begin by loading the packages to be used.

pkg.qmd

@@ -1,5 +1,8 @@
 ---
 title: "Package management and reproducible environments"
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 *Julius Krumbiegel also has a [great blog post](https://jkrumbiegel.com/pages/2022-08-26-pkg-introduction/) with more details on Julia environments.*

power_simulation.qmd

@@ -1,7 +1,9 @@
 ---
 title: "Using simulation to estimate uncertainty and power"
 subtitle: "Or how I learned how to stop worrying and love the bootstrap"
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 format:
   html:
     embed-resources: true

profiling.qmd

@@ -1,6 +1,9 @@
 ---
 title: "Confidence intervals from profiled objective"
 author: "Douglas Bates"
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 # Assessing the variability of parameter estimates

selection.qmd

@@ -1,5 +1,7 @@
 ---
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 ```{julia}

shrinkageplot.qmd

@@ -1,6 +1,8 @@
 ---
 title: "More on shrinkage plots"
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
   - I have stated that the likelihood criterion used to fit linear mixed-effects can be considered as balancing fidelity to the data (i.e. fits the observed data well) versus model complexity.

singularity.qmd

@@ -1,6 +1,9 @@
 ---
 title: "Convergence, singularity and all that"
 author: "Douglas Bates"
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 ## What does it mean for a converged model to be singular?
@@ -34,7 +37,7 @@ The covariance matrix for each subject's random effects is evaluated from its "m
 
 ```{julia}
 λ = only(m01.λ)
-``` 
+```
 
 The *transpose* of $\lambda$, written $\lambda'$, is an upper triangular matrix generated by "flipping" $\lambda$ about the main diagonal.
 

sleepstudy.qmd

@@ -1,6 +1,8 @@
 ---
 title: Analysis of the sleepstudy data
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 The `sleepstudy` data are from a study of the effects of sleep deprivation on response time reported in  @Balkin2000 and in @Belenky2003.

sleepstudy_speed.qmd

@@ -1,6 +1,8 @@
 ---
 title: "The sleepstudy: Speed - for a change ..."
-jupyter: julia-1.9
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 # Background

useful_packages.qmd

@@ -1,6 +1,9 @@
 ---
 title: "Useful packages"
 author: "Phillip Alday"
+engine: julia
+julia:
+  exeflags: ["--project", "--threads=auto"]
 ---
 
 Unlike R, Julia does not immediately expose a huge number of functions, but instead requires loading packages (whether from the standard library or from the broader package ecosystem) for a lot of relevant functionality for statistical analysis.
@@ -14,7 +17,7 @@ This has two important implications:
 
 This notebook is not intended to be an exhaustive list of packages, but rather to highlight a few packages that I suspect will be particularly useful.
 Before getting onto the packages, I have one final hint: take advantage of how easy and first-class package management in Julia is.
-Having good package management makes reproducible analyses much easier and avoids breaking old analyses when you start a new one. 
+Having good package management makes reproducible analyses much easier and avoids breaking old analyses when you start a new one.
 The package-manager REPL mode (activated by typing `]` at the `julia>` prompt) is very useful.
 
 # Data wrangling