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.
eda_pettitt_test(data, years, alpha = 0.05)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.
Numeric vector of observed annual maximum series values. Must be strictly positive, finite, and not missing.
Numeric vector of observation years corresponding to data.
Must be the same length as data and strictly increasing.
Numeric scalar in \([0.01, 0.1]\). The significance level for confidence intervals or hypothesis tests. Default is 0.05.
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
plot_pettitt_test(), eda_mks_test()
data <- rnorm(n = 100, mean = 100, sd = 10)
years <- seq(from = 1901, to = 2000)
eda_pettitt_test(data, years)
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