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arXiv · 1110.1364

Estimation of the Number of Spikes, Possibly Equal, in the High-Dimensional Case

Damien Passemier·Jian-Feng Yao
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Abstract

Estimating the number of spikes in a spiked model is an important problem in many areas such as signal processing. Most of the classical approaches assume a large sample size $n$ whereas the dimension $p$ of the observations is kept small. In this paper, we consider the case of high dimension, where $p$ is large compared to $n$. The approach is based on recent results of random matrix theory. We extend our previous results to a more difficult situation where some spikes are equal, and compare our algorithm to an existing benchmark method.

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Damien Passemier, Jian-Feng Yao. 2014-06-03. Estimation of the Number of Spikes, Possibly Equal, in the High-Dimensional Case. https://doi.org/10.1016/j.jmva.2014.02.017

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