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Cramèr-Rao Bound for Estimation After Model Selection and its Application to Sparse Vector Estimation

In many practical parameter estimation problems,
such as coefficient estimation of polynomial regression, the true
model is unknown and thus, a model selection step is performed
prior to estimation. The data-based model selection step affects
the subsequent estimation. In particular, the oracle Cramér-Rao
bound (CRB), which is based on knowledge of the true model, is
inappropriate for post-model-selection performance analysis and
system design outside the asymptotic region. In this paper, we

Categories:
Statistical Signal Processing
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