Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 224 for “"LASSO"”.
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Network inference via clustered fused graphical lasso
Embargo set by: Seth Robbins for item 107307 Lift date: 2020-09-04T20:37:00Z Reason: Author requested U of Illinois access only (OA after 2yrs) in Vireo ETD system
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The LASSO linear mixed model for mapping quantitative trait loci
… least absolute selection and shrinkage operator (LASSO). This method has the appealing ability to produce predictions of effects that are identically zero. The LASSO can also be specified as a random model where the effects follow a double exponential distribution. In this thesis, the LASSO is …
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Insights into rotaxane formation enable cyclase engineering for lasso peptide diversification
Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2026-12-01
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LASSO-OPTIMAL SUPERSATURATED DESIGN AND ANALYSIS FOR FACTOR SCREENING IN SIMULATION EXPERIMENTS
Complex systems such as large-scale computer simulation models typically involve a large number of factors. When investigating such a system, screening experiments are often used to sift through these factors to identify a subgroup of factors that most significantly influence the interested …
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Network Analysis of the Financial Sector: A Comprehensive Perspective with Adaptive Joint LASSO Method
… absolute shrinkage and selection operator (AJ LASSO). The innovation in this method is that it accounts for possible sparsity both in the coefficient and the covariance matrix of the estimated Vector autoregressive (VAR) model. The method is especially suitable for high-dimension network …
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Real Time Frequency Analysis of Signals From Lasso Catheter For Radiofrequency Ablation During Atrial Fibrillation
… spectrum analysis of signals obtained through lasso catheter during radiofrequency ablation of pulmonary vein was performed to determine the channel with dominant frequency. Threshold algorithm was used for signals which could be classified as type I and type II AF. Type III AF Signals which …
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A Comparison of Logistic, RIDGE, and LASSO Regression with Heart Failure Risk Data: Effects of Sample Size, Predictor Correlation, and Predictor Weight on Outcome Accuracy
<p>Logistic Regression (LR), LASSO regression, and RIDGE regression are standard classification techniques for predicting a dichotomous output. Since these methods are applied for similar purposes and have different features, it is crucial to evaluate the performance of these methods under …
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New progress in hot-spots detection, partial-differential-equation-based model identification and statistical computation
… Least Absolute Shrinkage and Selection Operator (Lasso) type problem. In this thesis, we have four main works. Chapter 1 and Chapter 2 fall in the first area, i.e., hot-spots detection in spatio-temporal data. Chapter 3 belongs to the second area, i.e., PDE-based model identification. Chapter 4 is …
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Volatility and return forecasting : time series and options-based methods
… least absolute shrinkage and selection operator (Lasso) based models in forecasting future log realized variance (RV) constructed from high-frequency returns. We conduct a comprehensive empirical study using the SPY and 10 individual stocks selected from 10 different sectors. In an in-sample …
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Characterization of a Novel Fis1 Interactor Required for Peripheral Distribution of the Mitochondrion of Toxoplasma Gondii
… the mitochondrion is maintained in a lasso shape that stretches around the parasite periphery and is in close proximity to the pellicle‚ suggesting the presence of membrane contact sites. Upon egress‚ these contact sites disappear‚ and the mitochondrion retracts and collapses towards …
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Variable selection in discrete survival models
… Least Absolute Shrinkage and Selection Operator (Lasso) and gradient boosting on discrete survival data. Parameter related mean squared errors (MSEs) and false positive rates suggest Lasso performs better than gradient boosting. Frailty models outperform discrete survival models that do not …
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Prediction of CYP3A4 metabolic activity from whole genome RNA-seq data with feature selection machine learning methods
… high-dimensionality of the dataset, we applied lasso and elastic net, two feature selection machine learning methods, for prediction and graphical lasso was used for constructing gene network graphs. A simulation study was performed to assess the performance of the prediction algorithms and to …
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Semiparametric Characteristics-based Models of Asset Returns
… unknown functions, they are solved by LASSO-style selection model and power enhanced hypothesis tests. The details of the three chapters are summarized below: Specification LASSO and an Application in Financial Markets This chapter proposes the method of Specification-LASSO in a …
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Neurologic And Metabolic Safety Of Fluoroquinolones
… validate two types of risk prediction models, LASSO and random forest, in predicting CNS and PNS dysfunction, which were outcomes found to be associated with fluoroquinolones in the first chapter. We assessed the accuracy and calibration of these models in a validation subset using AUC and …
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Robust methods for analyzing multivariate responses with application to time-course data
… number of methods have been developed including Lasso. The group Lasso is an extension of the Lasso with the goal of selecting important groups of variables rather than individual variables. In the third part of the dissertation, we propose two robust group Lasso algorithms for the multivariate …
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Sparsity and robustness in modern statistical estimation
… statistical models, with examples including the Lasso and matrix completion. At the same time, statistical models need to be robust--they should perform well when data is noisy--in order to make reliable decisions. While sparsity and robustness are often closely related, the exact relationship …
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Bayesian generalized additive model selection
… least absolute shrinkage and selection operator (LASSO) priors. Two types of priors are explored for the sparse fits. The first, Laplace-Zero and Grouped Lasso-Zero priors, is applied to Gaussian and binary responses. The second, (Grouped) Horseshoe priors, is used for Gaussian and count …
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Inference of high-dimensional linear models with time-varying coefficients
… nonparametric kernel smoothing technique and a Lasso bias-corrected ridge regression estimator using a bias-variance decomposition to address non-stationarity in the model. A hypothesis testing setup with familywise error control is presented alongside synthetic data and a real application to …
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The rhetoric of Orlando di Lasso's contributions to the Divine Offices of Matins and Lauds : a study of the relationship between liturgy, text and music
The music of Orlando di Lasso has long been regarded as a touchstone of sixteenth-century musical rhetoric. Using this assumption as a starting point, the present thesis is a detailed investigation of the rhetoric of the composer's works written for the Divine Offices of Matins and Lauds, a …
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