Time-series analysis.
Overview
| Works: | 246 works in 116 publications in 116 languages | |
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Titles
Time series analysis :nonstationary and noninvertible distribution theory /
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Applied time series analysis for business and economic forecasting /
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Chaos in real data :the analysis of non-linear dynamics from short ecological time series /
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Forecasting, structural time series models, and the Kalman filter /
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Modelling non-stationary economic time series :a multivariate approach /
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A handbook of time-series analysis, signal processing and dynamics /
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Time-Frequency and Time-Scale Methods :Adaptive Decompositions, Uncertainty Principles, and Sampling /
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Neural Networks and Sea Time SeriesReconstruction and Extreme-Event Analysis /
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Ordinal time series analysismethodology and applications in management strategy and policy /
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Handbook of time series analysisrecent theoretical developments and applications /
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Design of observer-based compensatorsfrom the time to the frequency domain /
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Mathematical methods in signal processing and digital image analysis /
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Volatility and time series econometricsessays in honor of Robert F. Engle /
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Time frequency signal analysis and processing :a comprehensive reference /
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Permutation complexity in dynamical systemsordinal patterns, permutation entropy and all that /
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Forecasting, structural time series models, and the Kalman filter /
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Climate time series analysisclassical statistical and bootstrap methods /
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Eddy current approximation of maxwell equationstheory, algorithms and applications /
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Time-series analysis :a comprehensive introduction for social scientists /
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Wiener chaosmoments, cumulants and diagrams : a survey with computer implementation /
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Natural time analysisthe new view of time : precursory seismic electric signals, earthquakes and other complex time series /
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Recursive estimation and time-series analysisan introduction for the student and practitioner /
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Practical time-frequency analysisGabor and wavelet transforms with an implementation in S /
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Money, capital formation and economic growthinternational comparison with time series analysis /
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Climate time series analysisclassical statistical and bootstrap methods /
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Control of cutting vibration and machining instabilitya time-frequency approach for precision, micro and nano machining /
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Non-linear optical response in atoms, molecules and clustersan explicit time dependent density functional approach /
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A time series approach to option pricingmodels, methods and empirical performances /
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Time series modeling for analysis and controladvanced autopilot and monitoring systems /
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Energy time series forecastingefficient and accurate forecasting of evolving time series from the energy domain /
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Indexation and causation of financial marketsnonstationary time series analysis method /
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Phenomenological structure for the large deviation principle in time-series statisticsa method to control the rare events in non-equilibrium systems /
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Compression-based methods of statistical analysis and prediction of time series
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Advances in time series methods and applicationsthe A. Ian Mcleod festschrift /
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State-space methods for time series analysis :theory, applications and software /
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Characterizing interdependencies of multiple time seriestheory and applications /
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Ensembles of type 2 fuzzy neural models and their optimization with bio-inspired algorithms for time series prediction
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Time series analysisnonstationary and noninvertible distribution theory /
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Advances in time series data methods in applied economic researchInternational Conference on Applied Economics (ICOAE) 2018 /
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Empirical likelihood and quantile methods for time seriesefficiency, robustness, optimality, and prediction /
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Linear models and time-series analysis :regression, ANOVA, ARMA and GARCH /
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Analysis and data-based reconstruction of complex nonlinear dynamical systemsusing the methods of stochastic processes /
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Multivariate time series analysis :with R and financial applications /
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Quantile regression for cross-sectional and time series dataapplications in energy markets using R /
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Enhanced Bayesian network models for spatial time series predictionrecent research trend in data-driven predictive analytics /
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Applied time series analysisa practical guide to modeling and forecasting /
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Copula-based Markov models for time seriesparametric inference and process control /
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Copula-based Markov models for time series :parametric inference and process control /
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Structural health monitoring by time series analysis and statistical distance measures
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Time-varying effect modeling for the behavioral, social, and health sciences
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Using artificial neural networks for timeseries smoothing and forecastingcase studies in economics /
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Unsupervised pattern discovery in automotive time seriespattern-based construction of representative driving cycles /
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Continuous time processes for financeswitching, self-exciting, fractional and other recent dynamics /
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Research papers in statistical inference for time series and related modelsessays in honor of Masanobu Taniguchi /
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Data driven model learning for engineerswith applications to univariate time series /
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Time and fractalsperspectives in economics, entrepreneurship, and management /
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