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Showing 1 to 3 of 3 for “"Smoothing parameter selection"”.
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Smoothing Parameter Selection In Nonparametric Functional Estimation
… to obtain completely data-driven choices of the smoothing parameter in functional estimation, within the confines of minimal assumptions. The focus of the study will be within the framework of the estimation of the distribution function, the density function and their multivariable extensions …
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Modeling Daily Power Demand in Southern Kentucky: A Single Household Approach
… by using the goodness of fit metric, AICCI, for smoothing parameter selection. The statistical workflow was executed using SAS and data was provided by the Glasgow Electric Plant Board of Barren County, Kentucky. Results show that LOESS outperformed the autoregressive model in roughly 80% of all …
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Fast and stable smoothing spline analysis of variance models for large samples with applications to electroencephalography data analysis
The current parameterization and algorithm used to fit a smoothing spline analysis of variance (SSANOVA) model are computationally expensive, making a generalized additive model (GAM) the preferred method for multivariate smoothing. In this thesis, I propose various approximations and algorithms to …