Pinned Repositories
adaslope
High dimensional linear regression with missing via adaptive SLOPE
bioconductor-workshop-1
disPEER_data
Centroids, geodesic distances and structural connectivity data used within disPEER paper
GSoC
Easy: download the development version of the R package SLOPE (devtools::install_github("jolars/SLOPE")). Fit SLOPE and lasso (hint: see the lambda argument in SLOPE()) models using the SLOPE package to the abalone data set that comes with SLOPE. Plot the results. What are the similarities and differences? Medium: write a function using RcppArmadillo that computes the proximal operator for SLOPE using Algorithm 3 (FastProxSL1) from Bogdan et al 2015 (SLOPE: adaptive variable selection via convex optimization). Compare the result with SLOPE:::prox_sorted_L1() (observe that this function uses a different algorithm than the one you are supposed to implement) Hard: write an R package using RcppArmadillo (as a backend) that uses FISTA or ADMM to solve ordinary least squares regression using SLOPE. Make use of the function to compute the proximal operator that you implemented in the previous test.
Lab2020
logreghd
Modern Logistic Regression for High Dimensional Data
R_Workshops
Materials for the workshops on statistical packages development in R at Mathematical Institute, University of Wrocław
Wyklad2020
ZPS2018
Zespolowy Projekt Specjalnosciowy
ZPS2018
Zespolowy Projekt Specjalnosciowy
AleksandraSteiner's Repositories
AleksandraSteiner/adaslope
High dimensional linear regression with missing via adaptive SLOPE
AleksandraSteiner/logreghd
Modern Logistic Regression for High Dimensional Data
AleksandraSteiner/bioconductor-workshop-1
AleksandraSteiner/disPEER_data
Centroids, geodesic distances and structural connectivity data used within disPEER paper
AleksandraSteiner/GSoC
Easy: download the development version of the R package SLOPE (devtools::install_github("jolars/SLOPE")). Fit SLOPE and lasso (hint: see the lambda argument in SLOPE()) models using the SLOPE package to the abalone data set that comes with SLOPE. Plot the results. What are the similarities and differences? Medium: write a function using RcppArmadillo that computes the proximal operator for SLOPE using Algorithm 3 (FastProxSL1) from Bogdan et al 2015 (SLOPE: adaptive variable selection via convex optimization). Compare the result with SLOPE:::prox_sorted_L1() (observe that this function uses a different algorithm than the one you are supposed to implement) Hard: write an R package using RcppArmadillo (as a backend) that uses FISTA or ADMM to solve ordinary least squares regression using SLOPE. Make use of the function to compute the proximal operator that you implemented in the previous test.
AleksandraSteiner/Lab2020
AleksandraSteiner/R_Workshops
Materials for the workshops on statistical packages development in R at Mathematical Institute, University of Wrocław
AleksandraSteiner/Wyklad2020
AleksandraSteiner/ZPS2018
Zespolowy Projekt Specjalnosciowy