PyLOESS
This is a vectorized implementation of LOESS that supports polynomial models. It is fast enough for bootstrap resampling for computing prediction intervals.
Installation
pip install pyloess
Usage
from pyloess import loess
# Generate some data
import numpy as np
np.random.seed(0)
x = np.random.uniform(0, 10, 100)
y = np.sin(x) + np.random.normal(0, 0.1, 100)
x_new = np.linspace(0, 10, 1000)
# Evaluate the loess model
y_new = loess(x, y, eval_x=x_new, span=0.33, degree=2)
1 maintainer
Metadata
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Release files for pyloess 0.1.0
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Source distribution (sdist)
| File | Size | Uploaded | |
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| pyloess-0.1.0.tar.gz | 4.0 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| pyloess-0.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 7.7 kB
Release files / pyloess-0.1.0.tar.gz
| Download URL | pyloess-0.1.0.tar.gz |
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| Size | 4.0 kB |
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Release files / pyloess-0.1.0-py3-none-any.whl
| Download URL | pyloess-0.1.0-py3-none-any.whl |
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| Size | 3.7 kB |
| Tags | Python 3 |
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