Fast PQLseq
Project description
PQLseqPy
PQLseqPy is a fast implementation of a PQLseq in Python. It is inspired by PQLseq (Sun et al. 2019; PMID: 30020412), with added flexibility and significant performance improvements.
✨ Features
- Supports Binomial family with logit link
- Order-of-magnitude faster than PQLseq
- Handles variance components (
tau1,tau2) with options:- Fixed values
- Inference from data
- Stable Newton-Raphson updates with adaptive step size
- Regularization for numerical stability
- Easy to use API similar to
statsmodels
📦 Installation
You can easily install PQLseqPy via Conda:
conda install -c bioconda PQLseqPy
🚀 Usage
import numpy as np
from PQLseqPy import GLMM
# Simulated data
n = 100
np.random.seed(0)
X = np.hstack((np.ones((n, 1)), np.random.randn(n, 2)))
Y = np.hstack((np.random.randint(0, 10, (n, 1)), np.random.randint(1, 10, (n, 1))))
G = np.random.randn(n, 500)
K = G @ G.T
# Fit model
res = GLMM(X, Y, K).fit()
# Summary
param, coef = res.summary()
print(param)
print(coef)
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