2 citations · 5 across the 6 of their papers we have counts for
6 papers
Robust Clustering for Time Series Using Spectral Densities and Functional Data Analysis
Diego Rivera-García, Luis Angel García-Escudero, Agustín Mayo-Iscar +1
In this work a robust clustering algorithm for stationary time series is proposed. The algorithm is based on the use of estimated spectral densities, which are considered as functi…
Robust clustering for functional data based on trimming and constraints
Diego Rivera-García, Luis Angel García-Escudero, Agustín Mayo-Iscar +1
Many clustering algorithms when the data are curves or functions have been recently proposed. However, the presence of contamination in the sample of curves can influence the perfo…
The Hierarchical Spectral Merger algorithm: A New Time Series Clustering Procedure
Carolina Euan, Hernando Ombao, Joaquin Ortega
We present a new method for time series clustering which we call the Hierarchical Spectral Merger (HSM) method. This procedure is based on the spectral theory of time series and id…
Quadratic forms of the empirical processes for the two sample problem for functional data
R. Bárcenas, J. Ortega, A. J. Quiroz
The use of quadratic forms of the empirical process for the two-sample problem in the context of functional data is considered. The convergence of the family of statistics proposed…
Time Series Clustering using the Total Variation Distance with Applications in Oceanography
Pedro C. Alvarez-Esteban, C. Euán, J. Ortega
An algorithm for determining stationary periods for time series of random sea waves is proposed in this work. This is a problem in which changes between stationary sea states are u…
Profile Likelihood Intervals for Quantiles in Extreme Value Distributions
A. Bolívar, E. Díaz-Francés, J. Ortega +1
Profile likelihood intervals of large quantiles in Extreme Value distributions provide a good way to estimate these parameters of interest since they take into account the asymmetr…