Ersin Yılmaz's repositories
Post-shrinage-estimators-for-high-dimensional-semiparametric-models
Post-shirnakge strategy for high-Dimensional Partially linear model based on smoothing splines
Multi-Response-Semiparametric-Additive-Model-esstimators
Functions for Local polynomial based semiparametric estimators
Parameter-selection-for-Nonparametric-regression
This repository involves many parameter selection criteria for the smoothing parameter selection for the five smoothing method that are kNN regression, Kernel smoothing, Local linear regression, B-spline, truncated power basis splines and smoothing splines.
Tobit-ridge-estimator
Function estimates the tobit regression model under multicollinearity with ridge modification
Additive_Local_Linear-estimators
Modified aditive local linear based estimators for semiparametric additive models.
Censored-Partially-linear-additive-models
Modified local linear estimators in partially linear additive models with right-censored data based on different censorship solution techniques
Censored-time-series
Shiny app for prediction of the right-censored time-series nonparametrically
Chapter-3-R-codes
Chapter3_Rcodes
Cloudceiling-data-example
Real data work for the nonparametric modeling of the right-censored time series
Nonparametric-Regression-in-Error-in-Variables
R codes and function for the nonparametric regression model estimation under error in variables.
Right-censored-linear-mixed-effect-model
Estimation of the right-censored data with linear mixed effects model basis on the penalized (regression) splines.
Semi-parametric-P-TTLS-estimator
New semiparametric regresson model estimator based on Pade approximation with Truncated total least squares (P-TTLS)
simcensdata-generating-randomly-right-censored-data
simcensdata is a function generates randomly right-censored data. It is developed to simulate the survival datasets.
SPAM-Review
My design for simulation with functions
streamlit-example
Example Streamlit app that you can fork to test out share.streamlit.io