An intro guide to fitting models with brms, with a focus on the Poisson distribution

Due to regulatory changes, cigarette prices often increase. In this project, we analyzed the effects of price changes on cigarette consumption in the United States.

I recently (Gow, 2026) proposed an extension to the data science “whole game” of R for Data Science (Wickham et al., 2023). In Gow (2026), I used Australian stock price data to illustrate the data curation process and, in this note, I use US bank “Call Report” data as a second illustration. In effect, I provide complete instructions for building a high-performance data library covering all Call Reports data provided by the FFIEC Bulk Data website that can be construction in less than ten minutes on fast hardware (or a couple of hours on an older machine). I also give a few brief demonstrations of how to use the curated data, with examples for both R and Python. I conclude by discussing challenges encountered during processing and offering some observations about AI and data curation.

Laporan ini bertujuan untuk menganalisis struktur data HCV menggunakan pendekatan aljabar matriks. Tahapan dimulai dengan pre-processing untuk menyeleksi variabel numerik dan menangani missing values. Fokus analisis meliputi perhitungan Matriks Korelasi untuk mengidentifikasi pola hubungan antar-variabel, serta Matriks Varians-Kovarians untuk mengukur penyebaran data. Terakhir, dilakukan perhitungan nilai dan vektor eigen untuk memahami karakteristik dimensi data tersebut.