Global ETD Search
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Showing 1 to 5 of 5 for “"penalized least squares"”.
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Structured Sparsity Promoting Functions: Theory and Applications
… We explore the effect of these functions on the penalized least squares problem and discuss several algorithms for solving this problem which rely on the particular structure of our functions. We then apply these methods to the total variation denoising problem from signal processing.</p>
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l0 Sparse signal processing and model selection with applications
… cyclic descent, which is called the L0LS-CD (l0 penalized least squares via cyclic descent) algorithm. The other method minimizes smooth approximations of sparsity measures including those of the l0 norm via the majorization minimization (MM) technique, which is called the QC (quadratic concave) …
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Shape based classification and functional forecast of traffic flow profiles
… of partially observed traffic profiles through Penalized Least squares (PLS) technique were also demonstrated. Functional methods outperform the conventional ARIMA model in both short and medium-term forecast horizons. In addition, performance of functional methods in forecasting beyond one hour …
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Robust Feature Screening Procedures for Mixed Type of Data
… idea of best subset selection methods, which use penalized L_0 regularization, is computationally too expensive for many modern statistical applications. A large number of variable selection approaches via various forms of penalized least squares or likelihood have been developed to select …
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Directionality in time series and its applications
A suite of seven statistics to detect directionality in time series is presented. Applications from various disciplines including business, environmental science, finance and medicine are considered. Models that allow for directionality are proposed, and methods of fitting these models are …