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 69 for “"nonlinear regression"”.
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A blocked orthogonalization method for nonlinear regression
<p>"The blocked orthogonalization algorithm for nonlinear regression developed in this work results from a study of matching problems having certain identifiable characteristics with algorithms which exploit those characteristics. The new algorithm represents an extension of an earlier algorithm by …
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Exploring nonlinear regression methods, with application to association studies
The field of nonlinear regression is a long way from reaching a consensus. Once a method decides to explore nonlinear combinations of predictors, a number of questions are raised, such as what nonlinear combinations to permit and how best to search the resulting model space. Genetic Association …
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Analysis of the Repeated Measurement Data using the Hierarchical Clustering and Nonlinear Regression Methods in Asthma Pharmacogenetic Study
… for the predicted PEFR was constructed by nonlinear regression method. RESULT: Among the 12 SNPs, the ADCY9 132007 T>C polymorphism was significantly associated with response to combination inhaler. The patients with CT or CC genotype at the ADCY9 132007 T>C polymorphism are more in well …
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Robust and Nonparametric Methods for Topology Error Identification and Voltage Calibration in Power Systems Engineering
… the unknown parameters of a network in a nonlinear regression model. We propose a solution using nonlinear regression techniques to identify the correct status of every line in the network by deriving a statistical model of the power flows and injections while employing Kirchhoff's Current …
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Quantile regression and the duration of unemployment
Powell (1986) proposed a quantile regression estimator for censored regression models on the basis of equivariance of quantiles to monotone transformations. In this thesis, censored quantile regression models are generalized using two-parameter Box-Cox transformation to relax the conventional …
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Algorithmic Approaches to Nonparametric Causal Inference
… a calibration technique based around linear regression which constructs imputation estimators with upper bounds on the asymptotic variance of the estimator. We show that this calibration procedure is applicable to any imputation estimator which may be semiparametric efficient and …
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Measurement and Modeling of Nitrate-Nitrogen Transport in Subsurface Bioreactors
… 16.7 cm, and 0.2 hr-1, respectively through a nonlinear regression approach. The results of this study will lead to a better understanding of nitrate-N transport through bioreactors, and consequently, the development of design standards and operating protocols for field-scale systems.
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The relationship between cognitive inhibition, mental illness, and creativity
… were conducted to examine linear relationships, nonlinear regression models were conducted to consider the presence of an inverted U-shaped relationship between mental illness and creativity, and hierarchical regression models were conducted to examine the potential of cognitive inhibition as a …
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DEVELOPMENT AND APPLICATIONS OF MACHINE/DEEP LEARNING TECHNIQUES IN FLUID DYNAMICS
… network is more accurate and efficient in nonlinear regression problems. Secondly, in view of the network structure, RBF approximation is deployed in each hidden layer of the new network (RBF-MLP-II), which exhibits stronger predictive capability than other counterparts. Thirdly, the …
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Characterizing the Mechanical Properties of Composite Materials Using Tubular Samples
… performed to illustrate the sensitivity of the nonlinear regression methods to error in the experimental data. Ideal test matrices are proposed to provide the best data sets for improved accuracy of the property estimates. With these values, the stress and strain states can be calculated through …
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Solar activity detection and prediction using image processing and machine learning techniques
… to solve the CDE problem using kernel-based nonlinear regression and moment-based density function reconstruction techniques. This method involves two main steps. In the first step, kernel-based nonlinear regression techniques are applied to predict the conditional moments of the target …
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Hydration and Water Distribution Studies of Heart Muscle by Nuclear Magnetic Relaxation
… from chicken, pork, and beef is investigated. Nonlinear regression analysis of the $\sp1$H transverse magnetization decay yields the best fit with three exponential components that are likely to correspond to three separate types of water proton compartments in the heart muscle. A deuterium …
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Measuring and modeling stream and air temperature relationships in a multiland use watershed of the central United States
… distance as discharge increased. Linear and nonlinear regression analyses were performed between Tw and air temperature (Ta) data at time scales ranging from 15 minute to seasonal time steps. Additionally, the linear Tw model used in the Soil and Water Assessment Tool (SWAT), and a new …
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Parametric modeling of dependence of bivariate quantile regression residuals' signs
… of that interval. We recommend two distinct regression methods to model the conditional probability of concordance. The first is a logistic regression with a logit link modified. The second one is a nonlinear regression method, where the outcome is modeled as a polynomial function of the …
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Estimating Transmissivity From the Water Level Fluctuations of a Sinusoidally Forced Well
… (1988). The estimates of T determined using nonlinear regression, time series analysis, and Rojstaczer (1988) were consistent in the absolute and relative magnitude for both wells. However, the estimates of transmissivity determined with these three methods were generally lower than the …
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Flexural behavior of a glass fiber reinforced wood fiber composite
… and observed creep deflections based on nonlinear regression estimates of model parameters.
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Simulation of deep-bed drying of Virginia peanuts to minimize energy use
… rates were fitted to the collected data using nonlinear regression techniques. The modified Page's model and the two-term exponential model fitted the data better than other models considered. A deep-bed drying model PEATECH based on four coupled partial differential equations consisting of …
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A Discrete Event Simulation of Network Centric Operations: Modeling Unbalanced Combat Configurations in Symmetric Engagements
… utilized agent-directed simulations. Linear and nonlinear regression analyses were conducted to highlight the performance metrics that wield significant predictive power over the probability of winning a combat engagement.</p>
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Hydration and activity studies of bovine skeletal muscle proteins and wheat gliadins by nuclear magnetic resonance
… Numerical analysis of the data was performed by nonlinear regression on an Apple-MacIntosh II microcomputer, using a thermodynamic linkage approach. The second virial coefficient, B$\sb{\rm o}$, of myosin $A$ and $B$ was obtained from the protein concentration dependence of the relaxation rates …
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