  In a spiked population model, the population covariance matrix has all its
eigenvalues equal to units except for a few fixed eigenvalues (spikes). This
model is proposed by Johnstone to cope with empirical findings on various data
sets. The question is to quantify the effect of the perturbation caused by the
spike eigenvalues. A recent work by Baik and Silverstein establishes the almost
sure limits of the extreme sample eigenvalues associated to the spike
eigenvalues when the population and the sample sizes become large. This paper
establishes the limiting distributions of these extreme sample eigenvalues. As
another important result of the paper, we provide a central limit theorem on
random sesquilinear forms.
