Sparsity of regression parameters or differential parameters is not necessary for consistent multiple change point detection in high-dimensional linear regression; a covariance discrepancy scan is statistically and computationally more efficient.
(M5) Using the same model parameters as in (M4), we now define Σt = n − t n − 1 · Σ(0)(0.3) + t − 1 n − 1 · Σ(1)(0.3)
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Detection and inference of changes in high-dimensional linear regression with non-sparse structures
Sparsity of regression parameters or differential parameters is not necessary for consistent multiple change point detection in high-dimensional linear regression; a covariance discrepancy scan is statistically and computationally more efficient.