Results 11 to 20 of about 19,312,029 (301)
Boosting nonlinear additive autoregressive time series [PDF]
Computational Statistics & Data Analysis, 2009 Within the last years several methods for the analysis of nonlinear autoregressive time series have been proposed. As in linear autoregressive models main problems are model identification, estimation and prediction. A boosting method is proposed that performs model identification and estimation simultaneously within the framework of nonlinear ...
Nivien Shafik, Gerhard Tutz 0001
openaire +4 more sources
Time series with tailored nonlinearities [PDF]
Physical Review E, 2015 It is demonstrated how to generate time series with tailored nonlinearities by inducing well- defined constraints on the Fourier phases. Correlations between the phase information of adjacent phases and (static and dynamic) measures of nonlinearities are established and their origin is explained. By applying a set of simple constraints on the phases of
Räth, Christoph, Laut, Ingo
openaire +5 more sources
Volatility of linear and nonlinear time series [PDF]
Physical Review E, 2005 Previous studies indicate that nonlinear properties of Gaussian time series with long-range correlations, $u_i$, can be detected and quantified by studying the correlations in the magnitude series $|u_i|$, i.e., the ``volatility''. However, the origin for this empirical observation still remains unclear, and the exact relation between the correlations ...
Tomer Kalisky +2 more
openaire +3 more sources
NoLiTiA: An Open-Source Toolbox for Non-linear Time Series Analysis
Frontiers in Neuroinformatics, 2022 In many scientific fields including neuroscience, climatology or physics, complex relationships can be described most parsimoniously by non-linear mechanics.
Immo Weber +2 more
doaj +1 more source
Preface "Extreme Events: Nonlinear Dynamics and Time Series Analysis" [PDF]
Nonlinear Processes in Geophysics, 2011 No abstract available.
H. W. Rust, P. Yiou, B. D. Malamud
doaj +1 more source
A new algorithm for latent state estimation in nonlinear time series models [PDF]
, 2008 We consider the problem of optimal state estimation for a wide class of nonlinear time series models. A modified sigma point filter is proposed, which uses a new procedure for generating sigma points.
Mamon, R, Date, P, Jalen, L
core +4 more sources
Boosting Techniques for Nonlinear Time Series Models [PDF]
, 2010 Many of the popular nonlinear time series models require a priori the choice of parametric functions which are assumed to be appropriate in specific applications.
Gerhard Tutz +5 more
core +1 more source
Forecasting With Nonlinear Time Series Models [PDF]
SSRN Electronic Journal, 2010 AbstractThis article considers nonlinear forecasting models, such as switching-regime models. These models are typically “small” compared to vector autoregressive and factor models, being either univariate or single-equation models, but tend to nest a linear relationship and so invite an assessment of whether allowing for nonlinearity improves forecast
Timo Terasvirta, Anders Bredahl Kock
openaire +1 more source
A partially linearized sigma point filter for latent state estimation in nonlinear time series models [PDF]
, 2010 A new technique for the latent state estimation of a wide class of nonlinear time series models is proposed. In particular, we develop a partially linearized sigma point filter in which random samples of possible state values are generated at the ...
Mamon, R, Date, P, Jalen, L
core +1 more source
Model-free prognostication of non-linear time series
PLoS ONEObjectiveThe COVID-19 pandemic has highlighted the importance of studying the course of infectious progression. Similar needs exist for time series of other origins.
Xiaoyong Wu +2 more
doaj +2 more sources