chainladder.DevelopmentCorrelation

class chainladder.DevelopmentCorrelation(triangle, p_critical: float = 0.5)

Mack (1997) test for correlations between subsequent development factors. Results should be within confidence interval range otherwise too much correlation

Parameters:

triangle: Triangle

Triangle on which to estimate correlation between subsequent development factors.

p_critical: float (default=0.5)

Value between 0 and 1 representing the confidence level for the test. A value of 0.5 implies a 50% confidence. The default value is based on the example provided in the Mack 97 paper, the selection of which is justified on the basis of the test being only an approximate measure of correlations and the desire to detect correlations already in a substantial part of the triangle.

Attributes:

t_critical: DataFrame

Boolean value for whether correlation is too high based on p_critical confidence level.

t_expectation: DataFrame

Values representing the Spearman rank correlation

t_variance: float

Variance measure of Spearman rank correlation

confidence_interval: tuple

Range within which t_expectation must fall for independence assumption to be significant.