Assessing extrema of empirical principal component functions
The difficulties of estimating and representing the distributions of functional data mean that principal component methods play a substantially greater role in functional data analysis than in more conventional finite-dimensional settings. Local maxima and minima in principal component functions are of direct importance; they indicate places in the domain of a random function where influence on the function value tends to be relatively strong but of opposite sign. We explore statistical...[Show more]
|Collections||ANU Research Publications|
|Source:||Annals of Statistics 2006, Vol. 34, No. 3, 1518-1544|
|Hall and Vial Assessing extrema 2006.pdf||309.75 kB||Adobe PDF|
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