python method for solving a Weighted Least Squares with non-diagonal weight matrix -

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मैं linalg.lstsq (A, y) का उपयोग कर रहा हूँ प्रकार y = ax ।

जब मैं एक विकृत वजन मैट्रिक्स डब्ल्यू के साथ एक WLS समस्या को हल करना चाहता हूं, तो मैं सुझाए गए समाधान का उपयोग कर सकते हैं और लागू कर सकते हैं:

< पूर्व> वा ए = ए * एनपी एसक्यूआरटी (एनपीडीओगोनाल (डब्ल्यू)) wy = y * np.sqrt (np.diagonal (w)) linalg.lstsq (wA, wy) [0]

हालांकि, अगर W विकर्ण नहीं है, तो यह काम नहीं करेगा। मैं विश्लेषणात्मक समाधान (के अनुसार) को लागू कर सकता हूँ: 

  ATWA = np.dot (np.dot (AT, W), ए) एटीवी = एनपी.डॉट (एनपी.डॉट (एटी) , W), y) linalg.lstsq (ATWA, ATWY) [0]

लेकिन मुझे आश्चर्य है कि अगर एक संभावना है, linalg का उपयोग कर, या कोई अन्य लाइब्रेरी , जैसे कुछ ही बुला: 

  हल (y, ए, डब्ल्यू)


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