eda_pettitt_test: Pettitt Test for Abrupt Changes in the Mean of a Time Series

Description

Performs the nonparametric Pettitt test to detect a single abrupt change in the central tendency of a time series. Under the null hypothesis, there is no change.

Usage

eda_pettitt_test(data, years, alpha = 0.05)

Value

A list containing the test results, including:

data: The data argument.
years: The years argument.
alpha: The significance level as specified in the alpha argument.
null_hypothesis: A string describing the null hypothesis.
alternative_hypothesis: A string describing the alternative hypothesis.
u_series: Numeric vector of absolute U-statistics for all years.
statistic: The test statistic and maximum absolute U-statistic.
bound: The critical value of the test statistic based on alpha.
change_points: A dataframe containing the potential change point.
p_value: An asymptotic approximation of the p-value for the test.
reject: Logical scalar. If TRUE, the null hypothesis was rejected.

change_points contains the years, test statistics, and p-values of each potential change point. If no change points were identified, change_points

is empty.

Arguments

data: Numeric vector of observed annual maximum series values. Must be strictly positive, finite, and not missing.
years: Numeric vector of observation years corresponding to data. Must be the same length as data and strictly increasing.
alpha: Numeric scalar in \([0.01, 0.1]\). The significance level for confidence intervals or hypothesis tests. Default is 0.05.

References

Pettitt, A.N., 1979. A Non-parametric Approach to the Change-point Problem. J. Royal Statistics Society 28 (2), 126–135. http://www.jstor.org/stable/2346729

Examples

Run this code

data <- rnorm(n = 100, mean = 100, sd = 10)
years <- seq(from = 1901, to = 2000)
eda_pettitt_test(data, years)