Shih Ching Fu's repositories
2024_SSA_SCV
tidymodels tutorial for the Statistical Society of Australia (SSA) statistical computing and visualisation tutorials
ASASSN-V-J003310.78-415928.6
Light curve data for ASASSN-V J003310.78+415928.6
bortle-et-al-2021
Slides for paper review of Bortle et al. (2021)
CIC_Carpentries_R_materials
Materials for Carpentries Workshops in R
circumference-radius-activity
Code for plotting results from circumference and radius measuring activity for Year 4/5s at Takari PS.
lmem-example
Example of fitting a linear mixed effect model
gao-bien-witten-2022
Paper review of Gao, Lucy L., Jacob Bien, and Daniela Witten. 2022. ‘Selective Inference for Hierarchical Clustering’. Journal of the American Statistical Association 0 (0): 1–11. https://doi.org/10.1080/01621459.2022.2116331.
gp-nonzero-meanfn
Simulation study of effect of mean function specification on GP regression.
gp-sandbox-thunderkat
Application of Gaussian process regression to a selection of light curves from ThunderKAT survey.
griffith-et-al-2021
Slides for paper review of Griffiths, Ryan-Rhys, Jiachen Jiang, Douglas J. K. Buisson, Dan R. Wilkins, Luigi C. Gallo, Adam Ingram, Alpha A. Lee, et al. 2021. “Modelling the Multiwavelength Variability of Mrk 335 Using Gaussian Processes.” The Astrophysical Journal 914 (2): 144. https://doi.org/10.3847/1538-4357/abfa9f.
hwang-et-al-2023
Slides for review of Hwang, Seung-gyu, Benjamin L’Huillier, Ryan E. Keeley, M. James Jee, and Arman Shafieloo. ‘How to Use GP: Effects of the Mean Function and Hyperparameter Selection on Gaussian Process Regression’. Journal of Cosmology and Astroparticle Physics 2023, no. 02 (February 2023): 014. https://doi.org/10.1088/1475-7516/2023/02/014.
li-li-shao-2021
Slides for review of Li, Zhao-Zhou, Lu Li, and Zhengyi Shao. “Robust Gaussian Process Regression Based on Iterative Trimming.” Astronomy and Computing 36 (July 1, 2021): 100483. https://doi.org/10.1016/j.ascom.2021.100483.
mclaughlin-mullaney-littlefair-2024
Slides for review of McLaughlin, Summer A. J., James R. Mullaney, and Stuart P. Littlefair. “Using Gaussian Processes to Detect AGN Flares.” arXiv, March 8, 2024. http://arxiv.org/abs/2403.05354.
nason-nonstationary-ts-workshop
Non-stationary time series workshop with Prof. Guy Nason
nicholson-aigrain-2022
Slides for paper review of Nicholson, Belinda A., and Suzanne Aigrain. “Quasi-Periodic Gaussian Processes for Stellar Activity: From Physical to Kernel Parameters.” Monthly Notices of the Royal Astronomical Society 515, no. 4 (August 18, 2022): 5251–66. https://doi.org/10.1093/mnras/stac2097.
omi-ceti
GP fitting to Mira (Omicron Ceti) lightcurve
python_for_r_users
UA Workshop: Python for R users
sharma-prince-bose-2023
Slides for paper review of Sharma, Ajay, Raj Prince, and Debanjan Bose. “Detection of Gamma-Ray Quasi-Periodic Oscillations in Non-Blazar AGN PKS 0521-36.” arXiv, December 19, 2023. https://doi.org/10.48550/arXiv.2312.12623.
SN-2019fck
Light curve data for SN 2019fck
sunnaker-et-al-2013
Paper review of Sunnåker, Mikael, Alberto Giovanni Busetto, Elina Numminen, Jukka Corander, Matthieu Foll, and Christophe Dessimoz. ‘Approximate Bayesian Computation’. PLOS Computational Biology 9, no. 1 (10 January 2013): e1002803. https://doi.org/10.1371/journal.pcbi.1002803.
tazi-et-al-2023
Slides for paper review of Tazi, Kenza, Jihao Andreas Lin, Ross Viljoen, Alex Gardner, Ti John, Hong Ge, and Richard E. Turner. “Beyond Intuition, a Framework for Applying GPs to Real-World Data.” arXiv, July 6, 2023. https://doi.org/10.48550/arXiv.2307.03093.
zhang-et-al-2023
Review of Zhang, Hao, Yu-Chen Wang, Tong-Jie Zhang, and Ting-ting Zhang. 2023. ‘Kernel Selection for Gaussian Process in Cosmology: With Approximate Bayesian Computation Rejection and Nested Sampling’. arXiv. https://doi.org/10.48550/arXiv.2304.03911.