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Showing 1 to 11 of 11 for “"Stationary Processes"”.

  1. Statistical process control of stationary processes

    The burnt-in rate for simulated stationary and invertible ARMA1, 1(u, v) time series is discovered to be [u^(2t)]*(v a?? 1)^2. Thereafter, the first comprehensive simulation study is done to evaluate the performance-effort tradeoff between optimal EWMAST and optimal ARMAST control charts. The …

    nus Repository record for Statistical process control of stationary processes (opens in a new tab)

  2. Estimating partial group delay

    … in the system have been eliminated. For weakly-stationary processes, estimators for partial group delay are proposed based on indirect and direct approaches. Conditions for weak consistency and asymptotic normality of the proposed estimators are obtained. Applications to a multiple test of …

    vt Repository record for Estimating partial group delay (opens in a new tab)

  3. Modeling and Simulation of Random Processes and Fields in Civil Engineering and Engineering Mechanics

    … on to research work in simulation of random processes and fields. Novel algorithms for simulating random processes and fields such as earthquakes, wind fields, and properties of functionally graded materials are discussed. Specifically, a methodology is presented to determine the Evolutionary …

    columbia-diss Repository record for Modeling and Simulation of Random Processes and Fields in Civil Engineering and Engineering Mechanics (opens in a new tab)

  4. Memory Properties Of Transformations Of Linear Processes And Symmetric Gini Correlation

    A large class of time series processes can be modeled by linear processes, including a subset of the fractional ARIMA process. Transformation of linear processes is one of the most popular topics in univariate time-series analysis in recent years. In this dissertation, we study the memory …

    mississippi Repository record for Memory Properties Of Transformations Of Linear Processes And Symmetric Gini Correlation (opens in a new tab)

  5. Inference of time series regression models with weakly dependent errors

    … series regression with dynamic regressors and stationary and weakly dependent errors. The second and third aspects are motivated by the recent surge of awareness that the stationarity assumption for the error is often too restrictive for real data. Some macroeconomic series are often observed …

    uiuc Repository record for Inference of time series regression models with weakly dependent errors (opens in a new tab)

  6. State space modelling of extreme values with particle filters

    … they could be. While the extreme values of a stationary time series are well understood, datasets of extremes often contain varying degrees of non-stationarity. How best to extend standard extreme value models to account for non-stationary series is a topic of ongoing research. The thesis …

    lancaster Repository record for State space modelling of extreme values with particle filters (opens in a new tab)

  7. Perturbation-based Control of Industrial Fed-batch Bioprocesses

    … of industrial-scale microbial fed-batch bioprocesses. Its focus is therefore on methods which are easy to implement in an industrial setting, which gives certain limitations on sensors, actuators and control systems. The main part of the work in the thesis concerns control of the microbial …

    lund Repository record for Perturbation-based Control of Industrial Fed-batch Bioprocesses (opens in a new tab)

  8. Non-stationary time-dependent ARMA random vibration modeling, analysis & SHM with wind turbine applications

    … are wind turbines, for which the non-stationary vibration response stems from the time-dependent structural dynamics, as well as the randomness and variability of the wind excitation and other operational and environmental variables. The development of effective methods for the …

    patras-thes Repository record for Non-stationary time-dependent ARMA random vibration modeling, analysis & SHM with wind turbine applications (opens in a new tab)

  9. Statistical models for extreme weather events

    … is often preferred for modelling extremes of non-stationary processes as the parameters are invariant to the choice of threshold; our approach may increase the possibility of this model being used more widely. Second, we propose an adjustment to the likelihood when implementing a spatial …

    lancaster Repository record for Statistical models for extreme weather events (opens in a new tab)

  10. Quantitative modeling and analysis with FMC-QE

    … performance values is done on the assumption of stationary processes and is based on fundamental laws of the performance analysis: Little's Law and the Forced Traffic Flow Law. Little's Law is used within the different hierarchical levels (horizontal) and the Forced Traffic Flow Law is the key to …

    potsdam-diss Repository record for Quantitative modeling and analysis with FMC-QE (opens in a new tab)