Explorerk's Stars
vugsus/coursera-machine-learning
Coursera's Machine Learning by Andrew Ng
pzhaonet/msg2020
现代统计图形 2020 版
rpittman188/fdaconcur
This is the fdaconcur package.
MGallow/GLASSOO
Penalized precision matrix estimation via block-wise coordinate descent (graphical lasso)
AnnaWysocki/Network-Penalty-Selection
Simulation comparing four methods for selecting the penalty parameter in the graphical lasso
cran/T4cluster
:exclamation: This is a read-only mirror of the CRAN R package repository. T4cluster — Tools for Cluster Analysis. Homepage: https://kisungyou.com/T4cluster/ Report bugs for this package: https://github.com/kisungyou/T4cluster/issues
thomasp85/patchwork
The Composer of ggplots
rstudio/blogdown
Create Blogs and Websites with R Markdown
whitefly/Data-Mining
code implements of <<Statistical learning methods>>
program-spiritual/DataAnalysisInAction
(Finished) Geek Time Data Analysis Practical 45 Lecture - Detailed notes containing markdown images mind map code data can be read directly code test
qiwsir/algorithm
sunxiaolong321/Python-Datastructure-and-algorithm
**大学MOOC网课数据分析与算法Python版(陈斌)课程代码
bioops/legume_network
conserved and specific legume co-expression networks
czarrar/causality_primer
Doraemonzzz/Advanced-Probability-Theory
记录本校高等概率论课程笔记
steadyfish/Project536
MATLAB Project for modelling covariance matrix of financial time series data as Generalized Wishart Process
resteorts/modern-bayes
Modern Bayesian statistics, STA 360/602, Duke University, Department of Statistical Science
cran/NonpModelCheck
:exclamation: This is a read-only mirror of the CRAN R package repository. NonpModelCheck — Model Checking and Variable Selection in Nonparametric Regression
tongtzeho/PKUCourse
北大计算机课程大作业
lib-pku/libpku
贵校课程资料民间整理
netchx/netch
A simple proxy client
trambakbanerjee/asus
An R package for adaptive SURE thresholding with side information.
khanhnamle1994/statistical-learning
Lecture Slides and R Sessions for Trevor Hastie and Rob Tibshinari's "Statistical Learning" Stanford course
AnestisTouloumis/ShrinkCovMat
Provides nonparametric Steinian shrinkage estimators of the covariance matrix that are suitable in high dimensional settings, that is when the number of variables is larger than the sample size.
chrissles/funcy
Aratrika-cs/James-Stein
Presentation on James-Stein Estimator
mjafin/shrinkage_da
Shrinkage Discriminant Analysis utilising James-Stein shrinkage
amadyba/modelSelection_FDA
Here, our project deals with the selection model when we have functional data by using the model-based clustering method, called FunFEM. And we apply our study on CO2 Emissions Dataset (Data from The World Bank) to cluster the countries according to CO2 emission in the world.
Erwangf/funHDDC-wavelet
funHDDC-wavelet is a functional data clustering method. It use the Discrete Wavelet Transform to decompose curves into multiple components (levels) then train a parcimonious gaussian mixture model on them.
sakuramomo1005/Functional-data-analysis-draft
The draft for the rotation project preconditioning on clustering functional data analysis