The Lag Analysis Tool is an interactive tool designed to help users analyze the effect of lagging one time series relative to another. This tool computes and visualizes correlations between two datasets at various lags, enabling users to identify lead-lag relationships or delays. It is particularly useful for understanding how changes in one variable may precede or follow changes in another.

Key Features:

1. Dynamic Input : Users can input two time series datasets as comma-separated lists and specify the maximum lag for analysis.
2. Interactive Visualization : A line chart displays the correlation values at different lags, highlighting significant peaks or troughs.
3. Customizable Lag Range : Users can define the range of lags (positive and negative) to analyze.
4. PDF Download : Export the generated lag analysis results and visualization as a PDF for sharing or reporting purposes.
5. Modern Design : Clean and stylish layout with vibrant colors and clear typography for better readability.
6. Self-Contained : The tool operates within its own container, ensuring it doesn’t interfere with the page header or footer.

Use Cases:

• Lead-Lag Analysis : Researchers can identify whether one dataset leads or lags another, such as stock prices, economic indicators, or sensor data.
• Causal Relationships : Analysts can explore potential causal relationships between variables by examining lagged correlations.
• Reporting : Professionals can export lag analysis charts to include in reports or presentations.

How It Works:

1. Introduction : Lag analysis measures the correlation between two time series as one series is shifted (lagged) relative to the other. Positive lags indicate the second series is delayed relative to the first, while negative lags indicate the first series is delayed.
2. Input Fields : Users enter two time series datasets as comma-separated lists and specify the maximum lag for analysis.
3. Visualization : The tool generates a line chart displaying the correlation values at different lags.
4. Export : Users can download the lag analysis results and visualization as a PDF for further use.