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Showing 1 to 5 of 5 for “"Discrete time series."”.

  1. Statistical self-similarity in time series from financial data & chaotic dynamical systems

    … to introduce statistical self-similarity for discrete time series. My thesis is divided into three parts:

    wfu Repository record for Statistical self-similarity in time series from financial data & chaotic dynamical systems (opens in a new tab)

  2. Estimating lower bounds for time series prediction error

    Research on how to evaluate the time series prediction algorithms are relatively under investigated compared to those to develop prediction algorithms. This research presents a way to estimate lower bounds for a time series prediction error by utilizing the conditional entropy rate, which allows us …

    mit Repository record for Estimating lower bounds for time series prediction error (opens in a new tab)

  3. Evaluating and comparing Gaussian forecasts for discrete process time series.

    … three research papers which focus on comparing a discrete time series processes to a discretized Gaussian autoregressive process and the traditional Gaussian autoregressive process. We first provide a brief introduction to relevant background information in chapter one. In the second chapter, we …

    baylor Repository record for Evaluating and comparing Gaussian forecasts for discrete process time series. (opens in a new tab)

  4. Filter-based multiscale entropy analysis of complex physiological time series

    … used in analyzing the complexity of physiologic time series. In this thesis, we re-interpret the averaging process in MSE as filtering a time series by a filter of a piecewise constant type. From this viewpoint, we introduce the {\it filter-based multiscale entropy} (FME) which filters a time

    syracuse-diss Repository record for Filter-based multiscale entropy analysis of complex physiological time series (opens in a new tab)

  5. Retail Price Time Series Imputation

    A regular, discrete time series is an ordered sequence of coarse-grained observations taken at fixed time intervals. Here we consider regular, discrete, retail price time series datasets acquired through crowdsourcing. Crowdsourcing is a means of data collection whereby independent individuals push …

    regina Repository record for Retail Price Time Series Imputation (opens in a new tab)