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[PoC] add low-rank fitting #134

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[PoC] add low-rank fitting #134

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10 changes: 7 additions & 3 deletions mgwr/gwr.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,13 +5,13 @@
import copy
from typing import Optional
import numpy as np
import numpy.linalg as la
from scipy import linalg as la
from scipy.stats import t
from scipy.special import factorial
from itertools import combinations as combo
from spglm.family import Gaussian, Binomial, Poisson
from spglm.glm import GLM, GLMResults
from spglm.iwls import iwls, _compute_betas_gwr
from spglm.iwls import iwls, _compute_betas_gwr, _low_rank_hat
from spglm.utils import cache_readonly
from .diagnostics import get_AIC, get_AICc, get_BIC, corr
from .kernels import *
Expand Down Expand Up @@ -257,7 +257,11 @@ def _local_fit(self, i):
wi = self._build_wi(i, self.bw).reshape(-1, 1) #local spatial weights

if isinstance(self.family, Gaussian):
betas, inv_xtx_xt = _compute_betas_gwr(self.y, self.X, wi)
betas, rank = _compute_betas_gwr(self.y, self.X, wi)
if rank < self.X.shape[1]:
inv_xtx_xt = _low_rank_hat(self.X)
else:
inv_xtx_xt = la.solve(self.X.T @ self.X, self.X)
predy = np.dot(self.X[i], betas)[0]
resid = self.y[i] - predy
influ = np.dot(self.X[i], inv_xtx_xt[:, i])
Expand Down
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