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huangziwei merged 15 commits into from
May 6, 2026
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refactor: Median #19

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33c2413
fix: circ_median early-exit and circ_median_ci index bug
huangziwei May 5, 2026
db93d03
fix: _circ_median_grouped failed at odd number bins
huangziwei May 6, 2026
a202add
fix: more median-related cleanup
huangziwei May 6, 2026
389237f
fix: even more median-related cleanup
huangziwei May 6, 2026
c451e73
fix: even more median-related cleanup
huangziwei May 6, 2026
c07dd1c
draft: circ_median(method="HL*")
huangziwei May 6, 2026
546011f
add: tests for circ_median(method="HL*")
huangziwei May 6, 2026
117de09
Change: _ANGLE_DECIMALS = 5 to 8
huangziwei May 6, 2026
2599fa0
change: docs
huangziwei May 6, 2026
097f8f5
update: docs
huangziwei May 6, 2026
38dee07
fix: minor bugs/neglects in descriptive.py
huangziwei May 6, 2026
88fde7f
fix: more cosmetic neglects
huangziwei May 6, 2026
229969a
fix: bug in _circ_mean_ci_bootstrap()
huangziwei May 6, 2026
24c9a3d
add: circ_mean_ci(interval="hdi"|"percentile")
huangziwei May 6, 2026
da56add
change: polish descriptive.py
huangziwei May 6, 2026
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40 changes: 29 additions & 11 deletions docs/docs/feature-checklist.md
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,8 @@
| **Measures of Central Tendency** | | | | | |
| Circular Mean | `circ_mean` | `mean(alpha)` | `circ_mean(alpha)` | `circ.mean` | `mean.circular` |
| Circular Mean CI | `circ_mean_ci` | `mean(alpha, ci=95)` | `circ_confmean` | - | `mle.vonmises.bootstrap.ci` |
| Circular Median | `circ_median` | `median` | `circ_median` | - | `median.circular`/`medianHL.circular` |
| Circular Median (Fisher/Mardia) | `circ_median` (method=`"deviation"`/`"count"`) [^median-grouped] | `median` | `circ_median` | - | `median.circular` |
| Hodges-Lehmann Median | `circ_median` (method=`"HL1"`/`"HL2"`/`"HL3"`) | - | - | - | `medianHL.circular`[^medianHL-broken] |
| Circular Median CI | `circ_median_ci` | - | - | - | - |
| Circular Quantile | `circ_quantile` | - | - | - | `quantile.circular` |
| **Measures of Spread & Dispersion** | | | | | |
Expand All @@ -17,12 +18,14 @@
| Circular Variance | `circ_var` | `var` | `circ_var` | `circ.disp` | `var.circular` |
| Circular Standard Deviation | `circ_std` | `std` | `circ_std` | - | `sd.circular` |
| Circular Dispersion | `circ_dispersion` | - | - | - | - |
| Circular Range | `circ_range` | - | - | `circ.range` | `range.circular` |
| Concentration Parameter (κ) | `circ_kappa` | `kappa` | `circ_kappa` | `est.kappa` | `A1inv` |
| **Higher-Order Statistics** | | | | | |
| Circular Moment | `circ_moment` | `moment` | `circ_moment` | `tri.moment` | `trigonometric.moment` |
| Circular Skewness | `circ_skewness` | `skewness` | `circ_skewness` | - | - |
| Circular Kurtosis | `circ_kurtosis` | `kurtoisis` | `circ_kurtosis` | - | - |
| **Distance & Pairwise Comparisons** | | | | | |
| Mean deviation | `circ_mean_deviation` | - | - | - | `meandeviation` |
| Mean deviation [^mean-dev] | `circ_mean_deviation` | - | - | - | `meandeviation` |
| Circular Distance | `circ_dist` | `cdist` | `circ_dist` | - | - |
| Pairwise Circular Distance | `circ_pairdist` | `pairwise_cdiff` | `circ_dist2` | - | `dist.circular` |

Expand Down Expand Up @@ -67,19 +70,20 @@

| Feature | H0 | PyCircStat2 | PyCircStat | CircStat (MATLAB) | CircStats (R) | circular (R) |
|---------------------|------------|--------------------|--------------|-------------------|---------------|--------------------|
| Kuiper’s Test | $\rho = 0$ | `circ_kuiper_test` | `kupier` | `circ_kuipertest` | `kuiper` | `kuiper.test` |
| Kuiper’s Test | $\rho = 0$ | `kuiper_test` | `kuiper` | `circ_kuipertest` | `kuiper` | `kuiper.test` |
| Rao’s Spacing Test | $\rho = 0$ | `rao_spacing_test` | `raospacing` | `circ_raotest` | `rao.spacing` | `rao.spacing.test` |
| Watson's Test | $\rho = 0$ | `watson_test` | - | - | `watson` | `watson.test` |
| Circular Range Test | $\rho = 0$ | `circ_range_test` | - | - | `circ_range` | `range.circular` |


### 3. Correlation & Regression
| Feature | PyCircStat2 | PyCircStat | CircStat (MATLAB) | CircStats (R) | circular (R) |
|-------------------------------|----------------|------------|-------------------|---------------|---------------------------|
| Circular-Circular Correlation | `circ_corrcc` | `corrcc` | `circ_corrcc` | `circ.cor` | `cor.circular` |
| Circular-Linear Correlation | `circ_corrcl` | `corrcl` | `circ_corrcl` | - | - |
| Circular-Circular Regression | `CCRegression` | - | - | `circ.reg` | `lm.circular(type="c-c")` |
| Circular-Linear Regression | `CLRegression` | - | - | - | `lm.circular(type="c-l")` |
| Feature | PyCircStat2 | PyCircStat | CircStat (MATLAB) | CircStats (R) | circular (R) |
|-----------------------------------------------|----------------|------------|-------------------|---------------|---------------------------|
| Circular-Circular Correlation | `circ_corrcc` | `corrcc` | `circ_corrcc` | `circ.cor` | `cor.circular` |
| Circular-Linear Correlation | `circ_corrcl` | `corrcl` | `circ_corrcl` | - | - |
| Circular-Circular Regression | `CCRegression` | - | - | `circ.reg` | `lm.circular(type="c-c")` |
| Circular-Linear Regression [^cl-resp] | `CLRegression` | - | - | - | `lm.circular(type="c-l")` |
| Linear-Circular Regression (harmonic) [^lc-resp] | `LCRegression` | - | - | - | - |



Expand Down Expand Up @@ -165,12 +169,26 @@ All circular distributions assume angles are on ``[0, 2π)``. Inputs are automat
| | PPF | `wrapstable.ppf` | - | - | - | - |
| | RVS | `wrapstable.rvs` | - | - | `rwrpstab` | - |
| | Fit | `wrapstable.fit` | - | - | - | - |
| Asymmetric Trangular | PDF | - | - | - | - | `dasytriangular` |
| Asymmetric Triangular | PDF | - | - | - | - | `dasytriangular` |
| Projected Normal | PDF | - | - | - | - | `dpnorm` |
| | RVS | - | - | - | - | `rpnorm` |

[^uniform]: $\rho=0$ stands for uniform distributed.
[^median]: $\theta$ stands for median.
[^F]: $F$ stands for distributions.
[^one-way]: Yet anothr one-way ANOVA.
[^one-way]: Yet another one-way ANOVA.
[^two-way]: Two-way ANOVA.
[^median-grouped]: For grouped data (non-uniform `w`), `circ_median` uses the
Mardia (1972) interpolation; the `method` argument is ignored on that path.
[^medianHL-broken]: As of `circular` 0.5-2 (CRAN, 2025-09-24), `medianHL.circular`
builds the pair-mean array but its C primitive calls the deviation median on
the original `x` instead of on the pair-means, so HL1/HL2/HL3 all return the
regular `median.circular` value. See Otieno (2002) §3.4 for the intended
algorithm.
[^mean-dev]: Different signatures: pycircstat2's `circ_mean_deviation(α, β)`
evaluates Fisher (1993) eq. 2.32 — `d(β) = π − (1/n)Σ|π−|αᵢ−β||` — at every
reference angle `β` (vector output). R's `meandeviation(x)` is the scalar
`d(median(x))`. Same formula, different evaluation points.
[^cl-resp]: Circular response, linear predictor.
[^lc-resp]: Linear response, circular predictor (harmonic regression à la
Pewsey et al. 2014, §8.4).
42 changes: 21 additions & 21 deletions examples/B1-Fisher-1993.ipynb
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