• Article  

      AAA Note on the Behaviour of Nonparametric Density and Spectral Density Estimators at Zero Points of their Support 

      Paparoditis Efstathios, E.; Politis, Dimitris Nicolas (2015)
      The asymptotic behaviour of nonparametric estimators of the stationary density and of the spectral density function of a stationary process have been studied in some detail in the last 50-60years. Nevertheless, less is ...
    • Article  

      Adaptive bandwidth choice 

      Politis, Dimitris Nicolas (2003)
      In this paper, we consider the problem of bandwidth choice in the parallel settings of nonparametric kernel smoothed spectra] density and probability density estimation. We propose a new class of 'plug-in' type bandwidth ...
    • Article  

      Artificial neural networks for earthquake prediction using time series magnitude data or Seismic Electric Signals 

      Moustra, M.; Avraamides, Marios N.; Christodoulou, Chris C. (2011)
      The aim of this study is to evaluate the performance of artificial neural networks in predicting earthquakes occurring in the region of Greece with the use of different types of input data. More specifically, two different ...
    • Article  

      Automatic Block-Length Selection for the Dependent Bootstrap 

      Politis, Dimitris Nicolas; White, H. (2004)
      We review the different block bootstrap methods for time series, and present them in a unified framework. We then revisit a recent result of Lahiri [Lahiri, S. N. (1999b). Theoretical comparisons of block bootstrap methods, ...
    • Article  

      Baxter’s inequality for triangular arrays 

      Meyer, M.; McMurry, T.; Politis, Dimitris Nicolas (2015)
      A central problem in time series analysis is prediction of a future observation. The theory of optimal linear prediction has been well understood since the seminal work of A. Kolmogorov and N. Wiener during World War II. ...
    • Article  

      Biological applications of time series frequency domain clustering 

      Fokianos, Konstantinos; Promponas, Vasilis J. (2012)
      Clustering methods are used routinely to form groups of objects with similar characteristics. Collections of time series datasets appear in several biological applications. Some of these applications require grouping the ...
    • Article  

      Bootstrap methods for dependent data: A review 

      Kreiss, J. -P; Paparoditis Efstathios, E. (2011)
      This paper gives a review on a variety of bootstrap methods for dependent data. The main focus is not on an exhaustive listing and description of bootstrap procedures but on general principles which should be taken into ...
    • Article  

      Bootstrap prediction intervals for linear, nonlinear and nonparametric autoregressions 

      Pan, L.; Politis, Dimitris Nicolas (2016)
      In order to construct prediction intervals without the cumbersome-and typically unjustifiable-assumption of Gaussianity, some form of resampling is necessary. The regression set-up has been well-studied in the literature ...
    • Article  

      Bootstrap prediction intervals for Markov processes 

      Pan, L.; Politis, Dimitris Nicolas (2014)
      Given time series data X1,…,Xn, the problem of optimal prediction of Xn+1 has been well-studied. The same is not true, however, as regards the problem of constructing a prediction interval with prespecified coverage ...
    • Article  

      Bootstrap technology and applications 

      Lbger, C.; Politis, Dimitris Nicolas; Romano, J. P. (1992)
      Bootstrap resampling methods have emerged as powerful tools for constructing inferential procedures in modern statistical data analysis. Although these methods depend on the availability of fast, inexpensive computing, ...
    • Conference Object  

      Cointegration and nonstationarity in the context of multiresolution analysis 

      Worden, K.; Cross, E. J.; Kyprianou, Andreas (Institute of Physics Publishing, 2011)
      Cointegration has established itself as a powerful means of projecting out long-term trends from time-series data in the context of econometrics. Recent work by the current authors has further established that cointegration ...
    • Article  

      Consistent Testing for Pairwise Dependence in Time Series 

      Fokianos, Konstantinos; Pitsillou, M. (2017)
      We consider the problem of testing pairwise dependence for stationary time series. For this, we suggest the use of a Box–Ljung-type test statistic that is formed after calculating the distance covariance function among ...
    • Article  

      Distribution theory for the studentized mean for long, short, and negative memory time series 

      McElroy, T.; Politis, Dimitris Nicolas (2013)
      We consider the problem of estimating the variance of the partial sums of a stationary time series that has either long memory, short memory, negative/intermediate memory, or is the first-difference of such a process. The ...
    • Article  

      Financial time series 

      Politis, Dimitris Nicolas (2009)
      The evolution of financial markets is a complicated real-world phenomenon that ranks at the top in terms of difficulty of modeling and/or prediction. One reason for this difficulty is the well-documented nonlinearity that ...
    • Article  

      A fine-tuned estimator of a general convergence rate 

      McElroy, T.; Politis, Dimitris Nicolas (2008)
      Summary A general rate estimation method based on the in-sample evolution of appropriately chosen diverging/converging statistics has recently been proposed by D.N. Politis [C. R. Acad. Sci. Paris, Ser. I, vol. 335, pp. ...
    • Conference Object  

      Frequency-domain characterization of Singular Spectrum Analysis eigenvectors 

      Leles, M. C. R.; Cardoso, A. S. V.; Moreira, M. G.; Guimaraes, H. N.; Silva, C. M.; Pitsillides, Andreas (Institute of Electrical and Electronics Engineers Inc., 2017)
      Singular Spectrum Analysis (SSA) is a nonparametric approach used to decompose a time series into meaningful components, related to trends, oscillations and noise. SSA can be seen as a spectral decomposition, where each ...
    • Article  

      High-dimensional autocovariance matrices and optimal linear prediction 

      McMurry, T. L.; Politis, Dimitris Nicolas (2015)
      A new methodology for optimal linear prediction of a stationary time series is introduced. Given a sample X1,…,Xn, the optimal linear predictor of Xn+1 is Xn+1 = Φ1(n)Xn + Φ2(n)Xn−1 + + Φn(n)X1. In practice, the coefficient ...
    • Article  

      Higher-order accurate polyspectral estimation with flat-top lag-windows 

      Berg, A.; Politis, Dimitris Nicolas (2009)
      Improved performance in higher-order spectral density estimation is achieved using a general class of infinite-order kernels. These estimates are asymptotically less biased but with the same order of variance as compared ...
    • Article  

      An improved divergence information criterion for the determination of the order of an ar process 

      Mantalos, Panagiotis; Mattheou, K.; Karagrigoriou, Alex (2010)
      In this article we propose a modification of the recently introduced divergence information criterion (DIC, Mattheou et al., 2009) for the determination of the order of an autoregressive process and show that it is an ...
    • Article  

      Integer-valued time series 

      Fokianos, Konstantinos (2009)
      Integer-valued time series data appear in several diverse applications. However, modeling and inference for these types of dependent data pose several questions and interesting problems. The method of generalized linear ...