Classical single-changepoint tests (Pettitt, Buishand, SNHT)

Wraps the three single-change tests that hydrology and climatology use as their standard vocabulary, from the trend package. All three test \(H_0\): no change against a single change in the mean, differing in how they measure it:

"pettitt"

a rank-based (Mann–Whitney) statistic — distribution-free and robust to outliers.

"buishand"

the Buishand range test, based on rescaled adjusted partial sums; assumes normality.

"snht"

the standard normal homogeneity test of Alexandersson, the reference method for detecting inhomogeneities in climate records.

Each reports a location and a p-value, and — unlike most engines here — that p-value is valid, because the location was not chosen from a larger model search.

Usage

trend_wrapper(x, test = c("pettitt", "buishand", "snht"), alpha = 0.05, ...)

Arguments

x

A numeric vector.

test

Which test to run. Defaults to "pettitt".

alpha

Significance level below which the changepoint is reported. Defaults to 0.05. A test that does not reject returns an empty result rather than an unsupported location.

...

Additional arguments passed to the trend function.

Value

A ggcpt object with the test's p_value and statistic on the changepoints tibble. The per-position test statistic is available through cpt_statistic().

References

Pettitt AN (1979). “A non-parametric approach to the change-point problem.” Journal of the Royal Statistical Society: Series C, 28(2), 126–135. doi:10.2307/2346729 .

Buishand TA (1982). “Some methods for testing the homogeneity of rainfall records.” Journal of Hydrology, 58(1–2), 11–27. doi:10.1016/0022-1694(82)90066-X .

Alexandersson H (1986). “A homogeneity test applied to precipitation data.” Journal of Climatology, 6(6), 661–675. doi:10.1002/joc.3370060607 .

See also

Other changepoint engines: bcp_wrapper(), beast_wrapper(), bfast_wrapper(), binsegrcpp_wrapper(), bocpd_wrapper(), cpm_wrapper(), cpop_wrapper(), cpt_wrapper(), decafs_wrapper(), ecp_wrapper(), envcpt_wrapper(), esac_wrapper(), fabisearch_wrapper(), fastcpd_wrapper(), fcov_wrapper(), fmean_wrapper(), fpop_wrapper(), geomcp_wrapper(), hdcov_wrapper(), hdreg_wrapper(), idetect_wrapper(), inspect_wrapper(), kcp_wrapper(), kwc_wrapper(), mcp_wrapper(), mosum_wrapper(), network_wrapper(), not_wrapper(), npmojo_wrapper(), nsp_wrapper(), ocd_wrapper(), pilliat_wrapper(), segmented_wrapper(), smuce_wrapper(), sn_wrapper(), strucchange_wrapper(), taylor_wrapper(), tguh_wrapper(), var_wrapper(), wbs2_wrapper(), wbs_wrapper(), wbsts_wrapper()

Examples

set.seed(2026)
x <- c(rnorm(60), rnorm(60, 2))
trend_wrapper(x, test = "pettitt")
#> ggcpt (changepoint detection result)
#>   Method:         pettitt
#>   Change in:       mean 
#>   Changepoints found: 1 
#>   CP convention:   left 
#>   Penalty:         alpha = 0.05 
#>   Series length:   120 
#> 
#> Changepoints:
#> # A tibble: 1 × 4
#>      cp cp_value  p_value statistic
#>   <int>    <dbl>    <dbl>     <dbl>
#> 1    60   -0.999 1.54e-14      3072
trend_wrapper(x, test = "snht")
#> ggcpt (changepoint detection result)
#>   Method:         snht
#>   Change in:       mean 
#>   Changepoints found: 1 
#>   CP convention:   left 
#>   Penalty:         alpha = 0.05 
#>   Series length:   120 
#> 
#> Changepoints:
#> # A tibble: 1 × 4
#>      cp cp_value p_value statistic
#>   <int>    <dbl>   <dbl>     <dbl>
#> 1    60   -0.999       0      59.1