diff options
Diffstat (limited to 'numpy/lib/function_base.py')
| -rw-r--r-- | numpy/lib/function_base.py | 60 |
1 files changed, 30 insertions, 30 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 558dfbe34..6d84627cd 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -3898,21 +3898,21 @@ def percentile(a, method : str, optional This parameter specifies the method to use for estimating the percentile. There are many different methods, some unique to NumPy. - See the notes for explanation. The options aligning with the R types - and the H&F paper are: - - * (H&F 1): 'inverted_cdf' - * (H&F 2): 'averaged_inverted_cdf' - * (H&F 3): 'closest_observation' - * (H&F 4): 'interpolated_inverted_cdf' - * (H&F 5): 'hazen' - * (H&F 6): 'weibull' - * (H&F 7): 'linear' (default) - * (H&F 8): 'median_unbiased' - * (H&F 9): 'normal_unbiased' - - Mainly for compatibility reasons, NumPy also supports the following - options which appear to be unique to NumPy: + See the notes for explanation. The options sorted by their R type + as summarized in the H&F paper [1]_ are: + + 1. 'inverted_cdf' + 2. 'averaged_inverted_cdf' + 3. 'closest_observation' + 4. 'interpolated_inverted_cdf' + 5. 'hazen' + 6. 'weibull' + 7. 'linear' (default) + 8. 'median_unbiased' + 9. 'normal_unbiased' + + The first three methods are discontiuous. NumPy further defines the + following discontinuous variations of the default 'linear' (7.) option: * 'lower' * 'higher', @@ -4177,21 +4177,21 @@ def quantile(a, method : str, optional This parameter specifies the method to use for estimating the quantile. There are many different methods, some unique to NumPy. - See the notes for explanation. The options aligning with the R types - and the H&F paper are: - - * (H&F 1): 'inverted_cdf' - * (H&F 2): 'averaged_inverted_cdf' - * (H&F 3): 'closest_observation' - * (H&F 4): 'interpolated_inverted_cdf' - * (H&F 5): 'hazen' - * (H&F 6): 'weibull' - * (H&F 7): 'linear' (default) - * (H&F 8): 'median_unbiased' - * (H&F 9): 'normal_unbiased' - - Mainly for compatibility reasons, NumPy also supports the following - options which appear to be unique to NumPy: + See the notes for explanation. The options sorted by their R type + as summarized in the H&F paper [1]_ are: + + 1. 'inverted_cdf' + 2. 'averaged_inverted_cdf' + 3. 'closest_observation' + 4. 'interpolated_inverted_cdf' + 5. 'hazen' + 6. 'weibull' + 7. 'linear' (default) + 8. 'median_unbiased' + 9. 'normal_unbiased' + + The first three methods are discontiuous. NumPy further defines the + following discontinuous variations of the default 'linear' (7.) option: * 'lower' * 'higher', |