The purrr package provides us a set of convenient functions (e.g., map, map_lgl, map_chr, map_int, and map_dbl) to manipulate each element in a list in R. The map function in purrr package can be considered as an alternative to for loops or lapply function, and can be easily integrated with…

In this blog, I will introduce a new R package chkptstanr, which allows checkpoints in stan. This feature is useful when you want to cache the model outputs by certain time steps or resume a long run at specific points due to an interruption. In general, this package can be…

In this blog, we focus on understanding and comparing the generative processes of analysis of variance (ANOVA) vs. linear mixed effects regression model (lmer) for discrete explanatory variables. Even though there has been an overall shift from ANOVA to lmer model in the community of science, it is still helpful…

The development of dplyr and purrr packages makes the workflow of R programming more smooth and flexible. The dplyr package provides an elegant way of manipulating data.frames or tibbles in a column-wise (e.g., select, filter, mutate, arrange, group_by, summarise and case_when) or row-wise (rowwise, c_across, and ungroup) manner. …

In this blog, I will provide a step-by-step instruction of how we can generate data from a mixed effect model and recover the parameters of the model with the simulated dataset. This simulation-based experiment can help us better understand the structure and generative process of the multilevel model with correlated…

Lewandowski-Kurowicka-Joe (LKJ) distribution is a very useful prior distribution for parameter estimation in correlation matrices, and is also tightly related to matrix factorizations such as Cholesky decomposition. …

With the development of dplyr or its umbrella package tidyverse, it becomes quite straightforward to perform operations over columns or rows in R. These column- or row-wise methods can also be directly integrated with other dplyr verbs like select, mutate, filter and summarise, making them more comparable with other functions…

I am looking for a general-purpose editor that can integrate and customize different features across all programming languages that I often use (e.g., R, Python, Julia and Javascript), and Visual Studio Code seems to be the best candidate for me. Here I will give a quick overview of the key…

This post provides an example of simulating data in a Multivariate Normal distribution with given parameters, and estimating the parameters based on the simulated data via Cholesky decomposition in stan. Multivariate Normal distribution is a commonly used distribution in various regression models and machine learning tasks. It generalizes the Normal…