seoncheolpark Goto Github PK
Name: Seoncheol Park
Type: User
Company: Hanyang University
Location: Seoul, South Korea
Seoncheol Park's Projects
a-beginner-guide-to-carry-out-extreme-value-analysis-with-codes-in-python
A beginner's guide to carry out extreme value analysis, which consists of basic steps, multiple distribution fitting, confidential intervals, IDF/DDF, and a simple application of IDF information for roof drainage design. The guide mainly focuses on extreme rainfall analysis. However, the basic steps are also suitable for other climatic or hydrologic variables such as temperature, wind speed or runoff.
book-compstat
Computational Statistics Book
book-counterprob
Counterexamples in Probability
book-crc-extremes
A minimal example of using bookdown to write a book for Chapman & Hall/CRC
book-lm
Linear Models Book
book-prob
a Probability book
brinla
Bayesian Regression with INLA
climate
The R climate package: an interface for downloading in-situ meteorological (and hydrological) dataset
climate_indices
Climate indices for drought monitoring, community reference implementations in Python
course-compstat
Computational Statistics Course
course-extremes
extreme value statistics course
course-fakestat
fake statistics course
course-prob
Fake probability class
course-spatstat
Spatial Statistics Course
course-statcomputing
Statistical Computing Website
course-timeseries
fake time series course
courseevt
R markdown website practice
cqregforest
composite quantile regression forests
downscaler
An R package for climate data bias correction and downscaling (part of the climate4R bundle)
drs
[NeurIPS 2022] (De-)Randomized Smoothing for Decision Stump Ensembles
edibble
Grammar of Experimental Design
eeover
Ellipse-Ellipse overlap area
evacloud
Extreme value analysis on R studio cloud
faster
Fast Lane to Learning R!
gams-in-r-course
Generalized Additive Models in R: A Free Interactive Course
geobr
Easy access to shapefiles of the Brazilian Institute of Geography and Statistics (IBGE) and other official spatial data sets of Brazil
github-classroom-for-teachers
google-car
Code for "Fine-scale spatiotemporal air pollution analysis using mobile monitors on Google Street View vehicles"
grf
Generalized Random Forests
heatoncomparison
Code for Heaton et al (in JABES, 2018)
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