Package: aaltobda 0.3.2
aaltobda: Functionality and Data for the Aalto Course on Bayesian Data Analysis
Functionality and Data for the Aalto University Course on Bayesian Data Analysis.
Authors:
aaltobda_0.3.2.tar.gz
aaltobda_0.3.2.zip(r-4.5)aaltobda_0.3.2.zip(r-4.4)aaltobda_0.3.2.zip(r-4.3)
aaltobda_0.3.2.tgz(r-4.4-any)aaltobda_0.3.2.tgz(r-4.3-any)
aaltobda_0.3.2.tar.gz(r-4.5-noble)aaltobda_0.3.2.tar.gz(r-4.4-noble)
aaltobda_0.3.2.tgz(r-4.4-emscripten)aaltobda_0.3.2.tgz(r-4.3-emscripten)
aaltobda.pdf |aaltobda.html✨
aaltobda/json (API)
# Install 'aaltobda' in R: |
install.packages('aaltobda', repos = c('https://avehtari.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/avehtari/bda_course_aalto/issues
Datasets:
- algae - Algae
- bioassay - Bioassay
- bioassay_posterior - Bioassay_posterior
- drowning - Drowning
- factory - Factory
- kilpisjarvi - Kilpisjarvi
- kilpisjarvi2022 - Kilpisjarvi2022
- windshieldy1 - Windshieldy1
- windshieldy2 - Windshieldy2
bayesbayesianbayesian-data-analysisbayesian-inferencebayesian-methodsbayesian-workflow
Last updated 21 hours agofrom:f344a527d9. Checks:OK: 7. Indexed: yes.
Target | Result | Date |
---|---|---|
Doc / Vignettes | OK | Nov 20 2024 |
R-4.5-win | OK | Nov 20 2024 |
R-4.5-linux | OK | Nov 20 2024 |
R-4.4-win | OK | Nov 20 2024 |
R-4.4-mac | OK | Nov 20 2024 |
R-4.3-win | OK | Nov 20 2024 |
R-4.3-mac | OK | Nov 20 2024 |
Exports:bioassaylpdmvnormdtnewlog_inv_logitlog1m_inv_logitmcse_quantileptnewqtnewrmvnormrtnew
Readme and manuals
Help Manual
Help page | Topics |
---|---|
algae | algae |
bioassay | bioassay |
bioassay_posterior | bioassay_posterior |
Unnormalized log-posterior for bioassay, assuming uniform prior | bioassaylp |
Computes the density of a multivariate normal distribution | dmvnorm |
drowning | drowning |
factory | factory |
kilpisjarvi | kilpisjarvi |
kilpisjarvi2022 | kilpisjarvi2022 |
Implementation of log(1 / (1 + exp(-x))) robust to over- and under-flow | log_inv_logit |
Implementation of log(1 - 1 / (1 + exp(-x))) robust to over- and under-flow | log1m_inv_logit |
Computes MCSE for quantile estimates based on independent draws | mcse_quantile |
Produces random draws from a multivariate normal distribution | rmvnorm |
The Student-t Distribution | dtnew ptnew qtnew rtnew StudentT |
windshieldy1 | windshieldy1 |
windshieldy2 | windshieldy2 |