A block-diagonal growth curve model

• We consider a variation of the growth curve (GC) model, referred to as the block-diagonal growth curve (BDGC) model, where the unknown regression coefficient matrix is constrained to be block-diagonal. A closed-form approximate maximum likelihood (AML) estimator for this model is derived based on the maximum likelihood principle. We analyze the statistical properties of this method theoretically and show that the AML estimate is unbiased and asymptotically statistically efficient for a large snapshot number. Via numerical examples in wireless communications, we also show that the proposed AML estimator can achieve excellent estimation accuracy.

Ämnesord

NATURVETENSKAP  -- Data- och informationsvetenskap -- Systemvetenskap, informationssystem och informatik (hsv//swe)

NATURAL SCIENCES  -- Computer and Information Sciences -- Information Systems (hsv//eng)

Nyckelord

Block-diagonal vectorization

Cramér-Rao bound

Generalized Khatri-Rao product

Growth curve model

Maximum likelihood estimation

Information technology

Informationsteknologi

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