Last updated: 2024-11-21

Checks: 2 0

Knit directory: online_tut/

This reproducible R Markdown analysis was created with workflowr (version 1.7.1). The Checks tab describes the reproducibility checks that were applied when the results were created. The Past versions tab lists the development history.

R Markdown file: up-to-date

Great! Since the R Markdown file has been committed to the Git repository, you know the exact version of the code that produced these results.

Repository version: be24a4b

Great! You are using Git for version control. Tracking code development and connecting the code version to the results is critical for reproducibility.

The results in this page were generated with repository version be24a4b. See the Past versions tab to see a history of the changes made to the R Markdown and HTML files.

Note that you need to be careful to ensure that all relevant files for the analysis have been committed to Git prior to generating the results (you can use wflow_publish or wflow_git_commit). workflowr only checks the R Markdown file, but you know if there are other scripts or data files that it depends on. Below is the status of the Git repository when the results were generated: 


Ignored files:
    Ignored:    .DS_Store
    Ignored:    .Rproj.user/
    Ignored:    analysis/.DS_Store
    Ignored:    code/.DS_Store

Untracked files:
    Untracked:  code/functions.R
    Untracked:  code/tut.cpp
    Untracked:  code/tut.o
    Untracked:  code/tut.so

Unstaged changes:
    Deleted:    analysis/license.Rmd
    Modified:   analysis/lynx.rmd

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These are the previous versions of the repository in which changes were made to the R Markdown (analysis/index.Rmd) and HTML (docs/index.html) files. If you’ve configured a remote Git repository (see ?wflow_git_remote), click on the hyperlinks in the table below to view the files as they were in that past version.

File Version Author Date Message
Rmd be24a4b Ziang Zhang 2024-11-21 workflowr::wflow_publish("analysis/index.rmd")
html c401920 Ziang Zhang 2024-11-21 Build site.
Rmd 2a37224 Ziang Zhang 2024-11-21 workflowr::wflow_publish("analysis/index.rmd")
Rmd bb32e24 Ziang Zhang 2024-11-20 Start workflowr project.

See here for an overview of the sGP model as well as its associated computational methods.

The package BayesGP is available on CRAN, which efficiently implements Gaussian process priors (including the sGP) for various Bayesian hierarchical models.

The package sGPfit is available on GitHub, which can be used for more advanced applications of the sGP prior, including fitting the exact process through the state-space representation.

Tutorials:

The tutorials are organized from more basic to more advanced. It is recommended to start with the first tutorial and proceed in order.