Function ridge_regression 

pub fn ridge_regression(
    y_json: &str,
    x_vars_json: &str,
    _variable_names: &str,
    lambda: f64,
    standardize: bool,
) -> String

Performs Ridge regression via WASM.

Ridge regression adds an L2 penalty to the coefficients, which helps with multicollinearity and overfitting. The intercept is never penalized.

Arguments

• y_json - JSON array of response variable values
• x_vars_json - JSON array of predictor arrays
• variable_names - JSON array of variable names
• lambda - Regularization strength (>= 0, typical range 0.01 to 100)
• standardize - Whether to standardize predictors (recommended: true)

Returns

JSON string containing:

• lambda - Lambda value used
• intercept - Intercept coefficient
• coefficients - Slope coefficients
• fitted_values - Predictions on training data
• residuals - Residuals (y - fitted_values)
• df - Effective degrees of freedom

Errors

Returns a JSON error object if parsing fails, lambda is negative, or domain check fails.