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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 20 for “"least squares methods"”.
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Least squares finite element methods for the Stokes and Navier-Stokes equations
… goal of this work is to define and analyze least squares finite element methods for the Stokes and Navier-Stokes equations that are practical and optimal in a systematic and rigorous way. To accomplish this task we begin by developing the least squares theory for the linear Stokes equations. …
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Canonical Variate Analysis and Related Methods with Longitudinal Data
… are taken: a maximum likelihood approach, a least squares approach, and a covariance structure analysis approach. All methods have in common that they hypothesize canonical variates which are stable over time. The maximum likelihood approach models the positions of the group means in the …
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Weak Calibration and Image-Based Rendering Algorithms
… adapt recent advances in statistically-unbiased least-squares methods to our image-based rendering approach. The point-based PIV involves equations with bilinear or higher-order data dependencies and we show how to efficiently estimate its parameters by adapting Leedan's and Meer's technique for …
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Trade and welfare effects of unilateral environmental regulation: The case of Malaysian palm oil
… by three-stage (3SLS) and two-stage (2SLS) least squares methods. The restricted reduced form equations are derived and used to evaluate the policy impacts.
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Determination of fertility rating (FR) in the 3-PG model for loblolly pine (Pinus taeda L.) plantations in the southeastern United States
… yet evaluating soil fertility remains one of the least understood aspects of forest science. Phytocentric and geocenctric approaches were used to assess soil fertility in loblolly pine plantations throughout their geographic range in the United States. The model to assess soil fertility using a …
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Censored Regression Models With Applications to Infrastructure Degradation Studies
… is bounded or censored. In these conditions, least squares methods are not appropriate, although they are widely used. This dissertation develops a generalization of the Tobit censored regression model using Student's t distribution instead of the normal. Thus additional flexibility is …
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Money, income, and prices: the velocity of money in nine major O.E.C.D. economies
… related quarterly and annual data by generalized least squares methods. Analysis of the relationship between money and income is conducted using annual and quarterly data. Regressions of two measures of the money stock on nominal income, and of money per unit of output on the price level are …
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Bayesian hierarchical modelling of dual response surfaces
… and to estimate the model coefficients using least squares methods. In this dissertation, a Bayesian hierarchical approach is proposed to model the dual response system so that the inherent hierarchical variance structure of the response can be modeled naturally. The Bayesian model is …
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Capital structure and dividend policy: evidence from emerging markets
… on a sample of Indian firms using Weighted Least Squares methodology. The third research paper applies panel data procedures to estimate and test a model of the determinants of leverage, using the entire population of non-financial quoted firms in Mauritius. The last two empirical papers …
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Robust methods for analyzing multivariate responses with application to time-course data
… can have dramatic impacts on the quality of the least squares methods. We use Huber's loss function in developing robust methods for time-course multivariate responses. We use spline basis expansion of the time-varying regression coefficients to reduce dimensionality, and downweight the influence …
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Graphical model driven methods in adaptive system identification
… termed the graphical expectation-maximization least squares (GEM-LS) algorithm, can utilize the reduced dimensional problems induced by the structure to improve the accuracy of the system identification problem in the low sample regime over conventional methods for linear learning with limited …
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Graphical model driven methods in adaptive system identification
… termed the graphical expectation-maximization least squares (GEM-LS) algorithm, can utilize the reduced dimensional problems induced by the structure to improve the accuracy of the system identification problem in the low sample regime over conventional methods for linear learning with limited …
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Anomalies in P wave velocities in the Tampico embayment, Gulf Coast of Mexico
… were computed by fitting polynomials by Least Squares methods to the vertical time-depth data. The analysis of the velocity data was done by computing the regional trend of the velocity maps in each case, and then computing the residuals, which show the relationships between velocities …
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A multi-regional adaptation of the ASSA2008 AIDS and Demographic Model for population projections
… Levenberg-Marquardt algorithm with nonlinear least squares methods, Rogers-Castro multi-exponential age schedules are fitted to the census/survey migration data in order to obtain parameters used to estimate migration rates in the model for the period 1996-2007. After 2007, migration rates …
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Compound-Gaussian-regularized inverse problems: theory, algorithms, and neural networks
… tomographic imaging. Model-based and data-driven methods are two prevalent classes of approaches used to solve linear inverse problems. Model-based methods incorporate certain assumptions, such as the image prior distribution, into an iterative estimation algorithm, often, as an example, solving a …
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Wildlife health in human-modified landscapes: epidemiology of tick-borne pathogens affecting black-backed jackals and caracals
… ratio (Body Mass Index) and residual (Ordinary Least Squares) methods, and morphometry was compared with historical datasets for each species. There was no apparent effect of sex, age class or location on body condition of jackals or caracals. Host-attached tick diversity was highest in urban …
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A new estimation procedure for linear combinations of exponentials
… Unlike the iterative maximum likelihood and least-squares methods for estimating the parameters for such a model, the new procedure is noniterative and can be easily applied. Also, in contrast to other non-iterative methods, error estimates are available for the parameter estimates yielded by …
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Adaptive error estimation in linearized ocean general circulation models
Data assimilation methods, such as the Kalman filter, are routinely used in oceanography. The statistics of the model and measurement errors need to be specified a priori. In this study we address the problem of estimating model and measurement error statistics from observations. We start by …
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Adaptive error estimation in linearized ocean general circulation models
Data assimilation methods, such as the Kalman filter, are routinely used in oceanography. The statistics of the model and measurement errors need to be specified a priori. In this study we address the problem of estimating model and measurement error statistics from observations. We start by …
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Methods of Approximation in hpk Framework for ODEs in Time Resulting from Decoupling of Space and Time in IVPs
… coordinates and time. Thus, space-time coupled methods of approximation are rather natural for obtaining numerical solutions of the mathematical models (IVPs) describing the evolutions. If we decouple space and time, i.e. if we assume the time derivatives to be constant for an instant of time, …