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Showing 1 to 7 of 7 for “"semiparametric method"”.

  1. Linear Mixed Model Robust Regression

    … a nonparametric model fit to the data. It is a semiparametric method by which incompletely or incorrectly specified parametric models can be improved through adding an appropriate amount of a nonparametric fit. We apply this idea of model robustness in the framework of the linear mixed model. …

    vt Repository record for Linear Mixed Model Robust Regression (opens in a new tab)

  2. Model Robust Regression Based on Generalized Estimating Equations

    … and a nonparametric prediction. MRR is a semiparametric method by which an incompletely or an incorrectly specified parametric model can be improved through adding an appropriate amount of a nonparametric fit. The combined predictor can have less bias than the parametric model estimate …

    vt Repository record for Model Robust Regression Based on Generalized Estimating Equations (opens in a new tab)

  3. Approximate Bayesian approaches and semiparametric methods for handling missing data

    … for the outcome variable. The proposed Bayesian method is also extended to incorporate the auxiliary information from full sample. In second paper (Chapter 3), a new Bayesian method using the Spike-and-Slab prior is proposed to handle the sparse propensity score estimation. The proposed method is …

    iastate Repository record for Approximate Bayesian approaches and semiparametric methods for handling missing data (opens in a new tab)

  4. Dual Model Robust Regression

    … and Birch (1996) have demonstrated an effective semiparametric method in the one regressor, single-model regression setting which is a "hybrid" of parametric and nonparametric fits. Using their techniques, we develop a dual modeling approach which is robust to misspecification in either or both …

    vt Repository record for Dual Model Robust Regression (opens in a new tab)

  5. Some Advanced Model Selection Topics for Nonparametric/Semiparametric Models with High-Dimensional Data

    … for evaluating nonlinear interaction effect in a semiparametric model. To address the first topic, we propose a new Bayesian variable selection approach via the graphical model and the Ising model, which we refer to the ``Bayesian Ising Graphical Model'' (BIGM). There are several advantages of our …

    vt Repository record for Some Advanced Model Selection Topics for Nonparametric/Semiparametric Models with High-Dimensional Data (opens in a new tab)

  6. Essays on time series and panel data econometrics

    … The first essay considers the bootstrap method for the covariates augmented Dickey-Fuller (CADF) unit root test suggested by Hansen (1995). It is known that the CADF test is very powerful. However, its limit distribution depends on the nuisance parameter, and thus inference is not …

    rice Repository record for Essays on time series and panel data econometrics (opens in a new tab)

  7. Essays on driving factors of migration: From regional to metro perspectives

    Tiebout (1956) put forth his influential “voting with their feet” theory that people move across regions to match their preferences for the optimal bundle of tax and government services. Other previous studies had emphasized the significant impacts of locational characteristics on individual moving …

    uiuc Repository record for Essays on driving factors of migration: From regional to metro perspectives (opens in a new tab)