Results 31 to 40 of about 2,902,055 (272)
Ordinal patterns in the Duffing oscillator: Analyzing powers of characterization [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2021 Ordinal patterns are a time-series data analysis tool used as a preliminary step to construct the permutation entropy, which itself allows the same characterization of dynamics as chaotic or regular as more theoretical constructs such as the Lyapunov exponent.
Ivan Gunther +2 more
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Statistical properties of the entropy from ordinal patterns
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2022 The ultimate purpose of the statistical analysis of ordinal patterns is to characterize the distribution of the features they induce. In particular, knowing the joint distribution of the pair entropy-statistical complexity for a large class of time series models would allow statistical tests that are unavailable to date.
E. T. C. Chagas +5 more
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Time-Delay Identification Using Multiscale Ordinal Quantifiers
Entropy, 2021 Time-delayed interactions naturally appear in a multitude of real-world systems due to the finite propagation speed of physical quantities. Often, the time scales of the interactions are unknown to an external observer and need to be inferred from time ...
Miguel C. Soriano, Luciano Zunino
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Frontiers in Artificial Intelligence, 2021 Subtype and Stage Inference (SuStaIn) is an unsupervised learning algorithm that uniquely enables the identification of subgroups of individuals with distinct pseudo-temporal disease progression patterns from cross-sectional datasets.
Alexandra L. Young +15 more
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20 years of ordinal patterns: Perspectives and challenges
Europhysics Letters, 2022 Abstract In 2002, in a seminal article, Bandt and Pompe proposed a new methodology for the analysis of complex time series, now known as Ordinal Analysis. The ordinal methodology is based on the computation of symbols (known as ordinal patters) which are defined in terms of the temporal ordering of data points in a time series, and whose
Leyva Callejas, Inmaculada +4 more
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Ordinal patterns in long‐range dependent time series [PDF]
Scandinavian Journal of Statistics, 2020 AbstractWe analyze the ordinal structure of long‐range dependent time series. To this end, we use so called ordinal patterns which describe the relative position of consecutive data points. We provide two estimators for the probabilities of ordinal patterns and prove limit theorems in different settings, namely stationarity and (less restrictive ...
Annika Betken +5 more
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Generating Correlated Ordinal Random Values [PDF]
, 2011 Ordinal variables appear in many field of statistical research. Since working with simulated data is an accepted technique to improve models or test results there is a need for providing correlated ordinal random values with certain properties like ...
Leisch, Friedrich +2 more
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Penalized Regression with Ordinal Predictors [PDF]
, 2008 Ordered categorial predictors are a common case in regression modeling. In contrast to the case of ordinal response variables, ordinal predictors have been largely neglected in the literature. In this article penalized regression techniques are proposed.
Gertheiss, Jan, Tutz, Gerhard
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Qualitative ordinal scales: the concept of ordinal range [PDF]
, 2004 Many practical problems of quality control involve the use of ordinal scales. Questionnaires planned to collect judgments on qualitative or linguistic scales, whose levels are terms such as "good," "bad," "medium," etc., are extensively used both in ...
Franceschini, Fiorenzo +6 more
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Ordinal Ridge Regression with Categorical Predictors [PDF]
, 2011 In multi-category response models categories are often ordered. In case of ordinal response models, the usual likelihood approach becomes unstable with ill-conditioned predictor space or when the number of parameters to be estimated is large relative to ...
Zahid, Faisal Maqbool
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