We propose some new tools for visualizing functional data and for identifying functional outliers. The proposed tools make use of robust principal component analysis, data depth and highest density regions. We compare the proposed outlier detection methods with the existing “functional depth” method, and show that our methods have better performance on identifying outliers in French male age-sp...

A robust principal component analysis can be easily performed by computing the eigenvalues and eigenvectors of a robust estimator of the covariance or correlation matrix. In this paper we derive the innuence functions and the corresponding asymptotic variances for these robust estimators of eigenvalues and eigenvectors. The behavior of several of these estimators is investigated by a simulation...

The paper discusses the need for robust unsupervised anomaly detection. We focus on an approach that employs robust principal component analysis (PCA) to detect malicious behaviour. By using robust PCA, we can overcome the problem that we have to have enough anomaly–free data in the training phase of a detection system.

In this paper we examine whether the quality of academic research can be accurately captured by a single aggregated measure such as a ranking. With Shanghai University’s Academic Ranking of World Universities as the basis for our study, we use robust principal component analysis to uncover the underlying factors measured by this ranking. Based on a sample containing the top 150 ranked universit...

Different algorithms for principal component analysis (PCA) based on the idea of projection pursuit are proposed. We show how the algorithms are constructed, and compare the new algorithms with standard algorithms. With the R implementation pcaPP we demonstrate the usefulness at real data examples. Finally, it will be outlined how the algorithms can be used for robustifying other multivariate m...

spatial patterns are useful descriptors of the horizontal structure in a plant population and may change over time as the individual components of the population grow or die out. but, whether this is the case for desert woody annuals is largely unknown. in the present investigation, the variations in spatial patterns of tribulus terrestris during different pulse events in semi-arid area of the ...

the writers of this research have studied seven variables including: precipitation, relative humidity, sunny hours, temperature average, temperature minimum, temperature maximum and sea level pressure, at sanandaj air station during 1964-1994. sanandaj air station has nearly 10966 days of complete data for these variables. a principal component analysis (pca) has been applied on this data; then...

1. introduction natural hazards have existed in all periods of human life, but nowadays due to the exponential growth of human and population density in all aspects of life, especially in high risk areas, human has been faced with major disasters such as the asia tsunami, hurricane katrina and the earthquake in sichuan of china with significant casualties even in developed countries. these haza...