Monograph
A living archive for learning, memory, and technical synthesis.
Monograph collects polished review articles, daily records, selected photography moments, and media reflections. It is both a public notebook and a knowledge source for future portfolio search.
Featured Article Series
Introduction to Time Series
A seven-part learning path on stationarity, dependence, ARMA, diagnostics, ARIMA/SARIMA forecasting, and exponential smoothing, written for practical understanding before heavy derivation.
From Observations to a Modelable Time Series
Why stationarity matters, how transformations remove changing structure, and what differencing does to the information in a series.
Understanding Dependence in Time Series
How autocovariance, autocorrelation, and linear filters reveal what the past contributes to the present.
ARMA Models as Dynamic Filters
How autoregressive feedback and moving-average innovations create memory, persistence, oscillation, and finite shock effects.
From Correlation Patterns to a Fitted Time-Series Model
How linear projection, PACF, and Yule-Walker equations turn lag relationships into candidate models and forecasts.