All work
Time Series · Environmental Statistics
Rainfall Time-series Forecasting
Analyzed monthly rainfall patterns using decomposition, modern forecasting approaches and Box–Jenkins methods.
Why this matters
Shows the ability to move from time-series structure to forecast design and uncertainty-aware interpretation.
The question
Problem
Model and forecast monthly rainfall data while accounting for seasonality, trend and time dependence.
The work
Approach
- 01
Visualized and decomposed the series.
- 02
Compared classical and modern approaches.
- 03
Used Box–Jenkins identification, estimation and diagnostic checking.
Verified evidence
What the analysis surfaced
Monthly observations
Years covered
Modeling approaches
The decision
Recommended action
- Use rolling forecast validation before operational deployment.
Capabilities demonstrated
Time-series EDAForecastingDiagnosticsEnvironmental analytics
Tools
RTime-series decompositionARIMAForecastingDiagnostics
Limits & responsible use
- Forecast reliability depends on structural stability and future climate patterns.