Search for dissertations about: "Normal estimation"
Showing result 21 - 25 of 147 swedish dissertations containing the words Normal estimation.
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21. Estimation in Multivariate Linear Models with Linearly Structured Covariance Matrices
Abstract : This thesis focuses on the problem of estimating parameters in multivariate linear models where particularly the mean has a bilinear structure and the covariance matrix has a linear structure. Most of techniques in statistical modeling rely on the assumption that data were generated from the normal distribution. READ MORE
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22. Lifetime modeling and management of transformers
Abstract : This work have studied and developed lifetime estimation methods for the power transformer and how these could be used for asset management purposes. It is researchperformed in the intersection of the fields of reliability theory, statistical analysis, and stochastic process theory applied to lifetime estimations and management of transformers. READ MORE
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23. Bayesian Modeling of Conditional Densities
Abstract : This thesis develops models and associated Bayesian inference methods for flexible univariate and multivariate conditional density estimation. The models are flexible in the sense that they can capture widely differing shapes of the data. The estimation methods are specifically designed to achieve flexibility while still avoiding overfitting. READ MORE
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24. Parallel computing in model-based process engineering
Abstract : Chemical processes are usually expensive to run. To optimise a process, we need to know how the process behaves, and this is usually accomplished by studying the process experimentally. However, experiments are very expensive, particularly if an existing plant has to shut down normal operation to conduct an experiment. READ MORE
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25. Essays on Panel Data with Multidimensional Unobserved Heterogeneity
Abstract : This thesis contributes to econometric methodology in terms of estimation and inference in static panel data models with unobserved multidimensional heterogeneity. When not properly accounted for, unobserved heterogeneity may introduce bias into the parameter estimates associated with covariates of interest, such as treatment indicators or determinants of macroeconomic indicators. READ MORE