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Showing 1 to 8 of 8 for “"Change point model"”.

  1. A nonparametric change point model for multivariate phase-II statistical process control.

    … (SPC) procedures are designed to detect a change in distribution when a possibly never-ending stream of observations is collected. Extensive study has been conducted with the purpose of detecting a shift in location (e.g. mean or median) when univariate observations are collected. Many …

    umn Repository record for A nonparametric change point model for multivariate phase-II statistical process control. (opens in a new tab)

  2. Outside Influence and Troop Deployment

    … does not influence troop deployment. Using a change-point model, I found that there was one point in troop deployment that was significant. On August 5, 2014, there was a drastic decrease in troop deployment. This was due to NATO stating that the mission in Afghanistan was complete and all …

    usm Repository record for Outside Influence and Troop Deployment (opens in a new tab)

  3. Three Papers on the Political Consequences of Oil Prices

    … First, I implement a Bayesian meta-regression model to assess the state of research on the natural resource curse, finding that the measurement of resources is one of the most important sources of the debate. In the second part of the dissertation, I turn to discussing the impact of fuel prices …

    wustl Repository record for Three Papers on the Political Consequences of Oil Prices (opens in a new tab)

  4. Gaussian processes for state space models and change point detection

    … processes (GPs) for enhanced time series modeling. We first cover different approaches for using Gaussian processes in time series problems. These are extended to the state space approach to time series in two different problems. We also combine Gaussian processes and Bayesian online …

    cambridge Repository record for Gaussian processes for state space models and change point detection (opens in a new tab)

  5. Computational methods for the analysis of next generation sequencing data

    … the new technology has required profound changes to the data analysis. There is a substantial need for computational methods that allow a convenient analysis of these overwhelmingly high-throughput data sets and address an increasing number of compelling biological questions which are now …

    njit Repository record for Computational methods for the analysis of next generation sequencing data (opens in a new tab)

  6. Some Advanced Semiparametric Single-index Modeling for Spatially-Temporally Correlated Data

    Semiparametric modeling is a hybrid of the parametric and nonparametric modelings where some function forms are known and others are unknown. In this dissertation, we have made several contributions to semiparametric modeling based on the single index model related to the following three topics: …

    vt Repository record for Some Advanced Semiparametric Single-index Modeling for Spatially-Temporally Correlated Data (opens in a new tab)

  7. Bayesian Adaptive Designs For Early Phase Clinical Trials

    … the highest efficacy and tolerable toxicity. A change-point model is used to reflect the fact that the dose-toxicity surface of the combinational agents may plateau at higher dose levels, and a flexible logistic model is proposed to accommodate the possible non-monotonic pattern for the …

    uthsc Repository record for Bayesian Adaptive Designs For Early Phase Clinical Trials (opens in a new tab)

  8. Mining a large shopping database to predict where, when, and what consumers will buy next

    Retailers with electronic point-of-sale systems continuously amass detailed data about the items each consumer buys (i.e. what item, how often, its package size, how many were bought, whether the item was on special, etc.). Where the retailer can also associate purchases with a particular …

    cape-town Repository record for Mining a large shopping database to predict where, when, and what consumers will buy next (opens in a new tab)