On the Statistical Meaning of Truncated Singular Value Decomposition
نویسنده
چکیده
Empirical data collected in practice usually are not exact. For various reasons it is often suggested in many applications to replace the original data matrix by some lower dimensional representation obtained via subspace approximation or truncation. The truncated singular value decomposition, for example, is one of the most commonly used representations. This note attempts to shed some light on the statistical meaning of this lower dimensional representation.
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