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Showing 1 to 4 of 4 for “"Time Series Estimation"”.

  1. Time series estimation in a spiked signal regime

    … good movies on Netflix. The development of estimation algorithms that properly handle missing data make data imputation and forecasting possible. The design of any estimation algorithm depends on the assumptions one can make on a given set of data. This thesis addresses the problem of …

    uiuc Repository record for Time series estimation in a spiked signal regime (opens in a new tab)

  2. Divide and recombine: Autoregressive models and STL+

    … are proposed and applied to the Akamai CIDR time series data. The Akamai network is one of the world's largest distributed-computing platforms, with more than 250,000 servers in more than 80 countries. It is responsible for 15-20 percent of all web traffic. We obtained 110 GB raw CIDR data …

    purdue-thes Repository record for Divide and recombine: Autoregressive models and STL+ (opens in a new tab)

  3. Microstructure markets, strategy and exchange rate determination.

    … with recently developed techniques in panel time series estimation, such as the Pooled mean-group (Pesaran and Smith 1995, Pesaran and Shin 1999, and Pesaran 2004), and especially the panel second step least squares with time-invariant variables (Panel 2SLS) (Atkinson 2014). The strategic …

    bournemouth Repository record for Microstructure markets, strategy and exchange rate determination. (opens in a new tab)

  4. Particle Filtering for Continuous Time Problems

    … in Bayesian inference. When data arrives in real time or sequentially, and instantaneous statistical reasoning is required, sequential Monte Carlo (SMC) methods, or particle filters, are used to estimate the posterior distribution in real time. A major challenge in particle filtering is estimating …

    cambridge Repository record for Particle Filtering for Continuous Time Problems (opens in a new tab)