Mar 11, 2026 · Fundamentals

Detecting Time‑Series Change Points with Grid Search and Piecewise Regression

This article shows how to turn change‑point detection into an optimization problem by exhaustively searching knot configurations with grid search, selecting the best model using a penalised likelihood criterion (BIC), and applying piecewise regression to automatically locate trend breakpoints, illustrated with R and Python code on California natural‑gas consumption data.

BICPythonR

0 likes · 12 min read

Detecting Time‑Series Change Points with Grid Search and Piecewise Regression

Model Perspective

Aug 10, 2022 · Fundamentals

How to Test Residuals for White Noise and Choose ARMA Models with AIC/BIC

This article explains why residuals of an ARMA model should be white noise, how to use the Q‑test to detect autocorrelation, and how AIC and BIC criteria balance model fit against complexity for selecting the most appropriate ARMA specification.

AICARMABIC

0 likes · 3 min read

How to Test Residuals for White Noise and Choose ARMA Models with AIC/BIC