Global ETD Search
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Showing 1 to 13 of 13 for “"Local polynomial regression"”.
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CROSS VALIDATION METHOD ON WEIGHTED ISOTONIC REGRESSION FOR NONPARAMETRIC REGRESSION FITTING
This thesis discusses the local polynomial regression and the isotonic regression method to solve the nonparametric regression problem subject to the non-decreasing condition. To solve the continuous isotonic regression problem, Pool Adjacent Violators Algorithm (PAVA) is used by updating the local …
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Bias Assessment and Reduction in Kernel Smoothing
When performing local polynomial regression (LPR) with kernel smoothing, the choice of the smoothing parameter, or bandwidth, is critical. The performance of the method is often evaluated using the Mean Square Error (MSE). Bias and variance are two components of MSE. Kernel methods are known to …
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Extrapolation and bandwidth choice in the regression discontinuity design
… contributions to the literature on the regression discontinuity (RD) design. The first two chapters develop approaches to the extrapolation of treatment effects away from the cutoff in RD and use them to study the achievement effects of attending selective public schools, known as exam …
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Testing the profitability of technical analysis in Singapore and Malaysian stock markets
… a pattern recognition algorithm based on local polynomial regression to identify technical chart patterns that is an improvement over the kernel regression approach developed by Lo, Mamaysky and Wang.
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Model robust regression: combining parametric, nonparametric, and semiparametric methods
In obtaining a regression fit to a set of data, ordinary least squares regression depends directly on the parametric model formulated by the researcher. If this model is incorrect, a least squares analysis may be misleading. Alternatively, nonparametric regression (kernel or local polynomial …
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Learning manifolds with the Parametrized Self-Organizing Map and Unsupervised Kernel Regression
… manifold learning algorithm Unsupervised Kernel Regression (UKR) is introduced as a counterpart to the classical Nadaraya-Watson estimator. In a nutshell, UKR requires very little parameters to be chosen a priori: In its simplest form, a UKR model is fully specified by the dimensionality of …
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Portfolio optimization with quantile-based risk measures
… use of a nonparametric statistical technique (local polynomial regression - LPR) for the estimation of the gradient. This gradient has interesting financial applications where quantile-based risk measures like the V aR and the shortfall are used: it can be used to calculate a portfolio …
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What is an adequate living wage level for South Africa?
… individuals' self-reported income levels using a local polynomial regression (locally estimated scatterplot smoothing or LOESS). The results showed that both methods led to similar results. A monthly living wage of at least R10,000 – R11,000 would allow South Africans to achieve a good QoL. In the …
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Divide and recombined for large complex data: Nonparametric-regression modelling of spatial and seasonal-temporal time series
… I briefly introduce one type of nonparametric regression method, namely local polynomial regression, followed by emphasis on one specific application of loess on time series decomposition, called Seasonal Trend Loess (STL). The chapter is closed by the introduction of D\&R; (Divide and …
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Bandwidth Selection Concerns for Jump Point Discontinuity Preservation in the Regression Setting Using M-smoothers and the Extension to hypothesis Testing
Most traditional parametric and nonparametric regression methods operate under the assumption that the true function is continuous over the design space. For methods such as ordinary least squares polynomial regression and local polynomial regression the functional estimates are constrained to be …
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Statistical Methods for Dating Collections of Historical Documents
… of words in texts using nonparametric regression techniques of local polynomial fitting with kernel weight to generalized linear models. We combine the estimated probability of occurrences of words of a text to estimate the probability of occurrence of a text as a function of its …
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TIME-VARYING MEDIATION EFFECTS WITH BINARY MEDIATOR IN SMOKING CESSATION STUDIES
… derive time-varying causal (in)direct effects. A local polynomial regression-based approach integrated with the mediational g-formula was proposed as a possible solution. Furthermore, since no other studies have studied time-specific mediation effects using a potential outcomes framework-based …