[scatter-regression-lowess] LOWESS Regression Scatter Plot

[MarkusNeusinger]

A scatter plot with LOWESS (Locally Weighted Scatterplot Smoothing) regression curve overlaid. Shows non-parametric trend line that adapts to local data patterns without assuming a specific functional form.

[claude]

✅ Spec ID: scatter-regression-lowess

Rationale: LOWESS (Locally Weighted Scatterplot Smoothing) is a distinct non-parametric regression method from linear and polynomial regression, adapting locally to data patterns without assuming a functional form.

This is a valid new specification. Related existing specs (scatter-regression-linear, scatter-regression-polynomial) use parametric models, while LOWESS is fundamentally different in its approach.

[github-actions]

✅ Specification Ready: scatter-regression-lowess

PR: #2862

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specification.md

scatter-regression-lowess: Scatter Plot with LOWESS Regression

Description

A scatter plot with a LOWESS (Locally Weighted Scatterplot Smoothing) regression curve overlaid. LOWESS is a non-parametric method that fits smooth curves by performing local weighted regressions at each point, adapting to local data patterns without assuming a specific functional form. This makes it ideal for exploring complex relationships where the underlying pattern is unknown or varies across the data range.

Applications

• Exploring non-linear relationships in exploratory data analysis where the true relationship is unknown
• Visualizing trends in economic data where patterns may change over different value ranges
• Analyzing biological dose-response curves that don't follow standard mathematical models

Data

• x (numeric) - Independent variable values plotted on the horizontal axis
• y (numeric) - Dependent variable values plotted on the vertical axis
• Size: 50-500 points recommended (LOWESS benefits from moderate sample sizes)
• Example: Data with a complex, non-linear relationship that varies across the x-axis range

Notes

• LOWESS curve should be visually distinct from scatter points (solid line, contrasting color)
• Use moderate smoothing bandwidth (frac ~0.3-0.5) as default for balanced smoothness
• Points should have moderate transparency (alpha ~0.5-0.7) to show density and the fitted curve clearly
• Include axis labels and descriptive title mentioning LOWESS smoothing
• Optional: Show confidence band around the LOWESS curve if library supports it
• The curve should appear smooth without excessive oscillation or overfitting to noise

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Next: Add approved label to merge this specification to main.

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