R | Chen Xing

To read 8 ChatGPT tools for R programming

Jan 28, 2024 1 min read R, ML

Textbook Text Mining with R Tutorial juliasilge.github.io/tidytext/ Sentiment Analysis: Introduction to the Syuzhet Package Definitons A token is a meaningful unit of text, most often a word, that we are interested in using for further analysis, and tokenization is the process of splitting text into tokens.

Jan 25, 2024 2 min read R

Learning Resource: Social Network Analysis

Check out igraph R-package 📦! Summary of Concepts See my notes in “Analyzing Social Media Networks with NodeXL: Insights from A Connected World” (Hansen et al. 2019), Chapter 3 Sections 3.

Nov 24, 2023 5 min read tutorial, R, quantitive-marketing

Incorporating Time-Invariant Covariates into PNBD II

Introduction In this post, we’ll continue discover the difference between the Cohort Modeling and the Extended PNBD Model with time-invariant covariates. Check here to see the previous post. Data Prepare First let’s import the transactional data, and select the customers who first purchase happened in 2017-2018.

Aug 26, 2022 7 min read R, PredictiveAnalytics, tutorial

Incorporating Time-Invariant Covariates into PNBD

Introducton The original Pareto-NBD Model is awesome, but it does not allow us to add any covariates. In some cases, the covariates may affect the purchase, or the attrition process, or both.

Aug 23, 2022 11 min read PredictiveAnalytics, R

Survival Analysis in R

Here is some tutorial notes for “Survival Analysis in R” course. Do patients taking the new drug survive longer than others? How fast do people get a new job after getting unemployed?

Aug 18, 2022 2 min read R, tutorial, PredictiveAnalytics

Beta distribution as a prior

Introduction The Beta distribution is a useful probability distribution when you want model uncertainty over a parameter bounded between 0 and 1. In this post, we’ll explore how the two parameters of the Beta distribution determine its shape.

Jul 25, 2022 2 min read Probability, R, tutorial

CLV Prediction in R

Introduction In the previous posts, we talked about the theoretical part of Pareto/NBD model. This time, we will go over the CLV prediction in R. Customer lifetime value (CLV) is

Jul 10, 2022 5 min read PredictiveAnalytics, Probability, R, tutorial

How to use DT table in blogdown?

The DT::datatable object often does not work appropriately in the blogdown post. How to solve this issue? It seems no good answers for this problem. DT + widgetframe 📦 is a potential solution.

Jul 8, 2022 3 min read R, tutorial

Add Floating TOC in Blogdown

How to add a floating TOC in my blogdown post?

Jun 30, 2022 2 min read R

Get Myself a New Blog

Testing wowchemy academic theme.

Jun 28, 2022 2 min read R

在RStudio中设置代理GitHub

设置代理在国内使用RStudio难以连接GitHub，需要设

Jun 26, 2022 1 min read R

Tidy Evaulation in R

tidyeval in function programming

May 16, 2022 5 min read R, tutorial

Why TBATS?

forecast with tbats model

May 7, 2022 6 min read R, tutorial, Forecast

Make RStudio Cloud as an Standalone App on Mac

RStudio Cloud 是用浏览器登陆的，但是快捷键有冲突。解决办法：点击 nativefier 进行

Apr 3, 2022 1 min read R

How to install modeltime.gluonts on iMac-Pro

安装modeltime.gluonts需要python环境，

Mar 22, 2022 3 min read R, Python, tutorial

tinytex package issue on Mac M1

The issue of installing tinytex package on Mac M1. When knitr LaTex file, the error message is like: ! sh: xelatex: command not found Solve: run this in your terminal (not in the R console):

Mar 14, 2022 1 min read R

Translate Column Names back and forth

在处理中文数据中，第一步就是翻译列名到英语。当我们分析完数据

Mar 11, 2022 1 min read R, tutorial

Tidymodels Ecosystem Tutorial

Tiydmodels Ecosystem I also hold this post on this RPub tutorial. Introduction First we should get a feeling of tidymodels ecosystem, and understand what each package does! Note that: Data

Sep 15, 2022 17 min read ML, R, tutorial

XGBoost in R Tutorial

Note that the original material is from Beginners Tutorial on XGBoost and Parameter Tuning in R. Introduction Last week, we learned about Random Forest Algorithm. Now we know it helps us reduce a model’s variance by building models on resampled data and thereby increases its generalization capability.

Jan 12, 2022 18 min read R, ML