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Rozprawy doktorskie na temat „Regressiya”

Autor: Grafiati

Data publikacji: 2 czerwca 2025

Data aktualizacji: 31 lipca 2025

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1

McCubbin, Courtney C. "Regressive Play| An Investigation of Regression in the Analytic Container." Thesis, Pacifica Graduate Institute, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=13426903.

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<p> This thesis is a heuristic, hermeneutic investigation into regression using the author's experience as a case study. Regressive play and the desire for deeper regression within the analytic container are explored, guided by the question: What is the experience of following one's impulse to regress to more and more primordial states, and what kind of psychological container is needed to facilitate that deepening both inter- and intrapersonally? The author details a history of regression beginning with Sigmund Freud and continuing to psychoanalyst Michael Balint's <i>basic fault,</i> object

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Jacobs, Mary Christine. "Regression Trees Versus Stepwise Regression." UNF Digital Commons, 1992. http://digitalcommons.unf.edu/etd/145.

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Many methods have been developed to determine the "appropriate" subset of independent variables in a multiple variable problem. Some of the methods are application specific while others have a wide range of uses. This study compares two such methods, Regression Trees and Stepwise Regression. A simulation using a known distribution is used for the comparison. In 699 out of 742 cases the Regression Tree method gave better predictors than the Stepwise Regression procedure.

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3

Hagos, Tesfamichael Marikos. "Estimation of phases for compliant motion : Auto-regressive HMM, multi-class logistic regression, Learning from Demonstration (LfD), Gradient descent optimization." Thesis, Luleå tekniska universitet, Rymdteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-65613.

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Kapur, Atul. "Role of Stochastic Forcing in ENSO Variability in a Coupled GCM." Scholarly Repository, 2008. http://scholarlyrepository.miami.edu/oa_theses/168.

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A systematic procedure is designed to evaluate the role of stochastic forcing (SF) in El Nino ? Southern Oscillation (ENSO) exhibited by coupled ocean-atmosphere general circulation models (CGCMs). The procedure is applied on a 163-year run of a CGCM which has realistic representation of ENSO and SF. The realism of ENSO in the CGCM is determined by statistical comparison with a 29-year global reanalysis product. SF is extracted from both the CGCM and reanalysis as residual atmospheric variability uncoupled to the ocean. Further, the Madden-Julian Oscillation (MJO) and non-MJO components are is

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5

Schwartz, Amanda Jo. "Adaptive Regression Testing Strategies for Cost-Effective Regression Testing." Diss., North Dakota State University, 2013. https://hdl.handle.net/10365/26926.

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Regression testing is an important but expensive part of the software development life-cycle. Many different techniques have been proposed for reducing the cost of regression testing. To date, much research has been performed comparing regression testing techniques, but very little research has been performed to aid practitioners and researchers in choosing the most cost-effective technique for a particular regression testing session. One recent study investigated this problem and proposed Adaptive Regression Testing (ART) strategies to aid practitioners in choosing the most cost-effective tec

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6

Williams, Ulyana P. "On Some Ridge Regression Estimators for Logistic Regression Models." FIU Digital Commons, 2018. https://digitalcommons.fiu.edu/etd/3667.

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The purpose of this research is to investigate the performance of some ridge regression estimators for the logistic regression model in the presence of moderate to high correlation among the explanatory variables. As a performance criterion, we use the mean square error (MSE), the mean absolute percentage error (MAPE), the magnitude of bias, and the percentage of times the ridge regression estimator produces a higher MSE than the maximum likelihood estimator. A Monto Carlo simulation study has been executed to compare the performance of the ridge regression estimators under different experimen

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7

Wong, Deanna A. "Cytokine profiles in regressing and non-regressing basal cell carcinomas." Thesis, The University of Sydney, 1998. https://hdl.handle.net/2123/27687.

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8

Sánchez, Lozano Enrique. "Continuous regression : a functional regression approach to facial landmark tracking." Thesis, University of Nottingham, 2017. http://eprints.nottingham.ac.uk/43300/.

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Facial Landmark Tracking (Face Tracking) is a key step for many Face Analysis systems, such as Face Recognition, Facial Expression Recognition, or Age and Gender Recognition, among others. The goal of Facial Landmark Tracking is to locate a sparse set of points defining a facial shape in a video sequence. These typically include the mouth, the eyes, the contour, or the nose tip. The state of the art method for Face Tracking builds on Cascaded Regression, in which a set of linear regressors are used in a cascaded fashion, each receiving as input the output of the previous one, subsequently redu

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9

Kazemi, Seyed Mehran. "Relational logistic regression." Thesis, University of British Columbia, 2014. http://hdl.handle.net/2429/50091.

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Aggregation is a technique for representing conditional probability distributions as an analytic function of parents. Logistic regression is a commonly used representation for aggregators in Bayesian belief networks when a child has multiple parents. In this thesis, we consider extending logistic regression to directed relational models, where there are objects and relations among them, and we want to model varying populations and interactions among parents. We first examine the representational problems caused by population variation. We show how these problems arise even in simple cases wit

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10

Zuo, Yanling. "Monotone regression functions." Thesis, University of British Columbia, 1990. http://hdl.handle.net/2429/29457.

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In some applications, we require a monotone estimate of a regression function. In others, we want to test whether the regression function is monotone. For solving the first problem, Ramsay's, Kelly and Rice's, as well as point-wise monotone regression functions in a spline space are discussed and their properties developed. Three monotone estimates are defined: least-square regression splines, smoothing splines and binomial regression splines. The three estimates depend upon a "smoothing parameter": the number and location of knots in regression splines and the usual [formula omitted] in smo

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11

Sullwald, Wichard. "Grain regression analysis." Thesis, Stellenbosch : Stellenbosch University, 2014. http://hdl.handle.net/10019.1/86526.

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Thesis (MSc)--Stellenbosch University, 2014.<br>ENGLISH ABSTRACT: Grain regression analysis forms an essential part of solid rocket motor simulation. In this thesis a numerical grain regression analysis module is developed as an alternative to cumbersome and time consuming analytical methods. The surface regression is performed by the level-set method, a numerical interface advancement scheme. A novel approach to the integration of the surface area and volume of a numerical interface, as defined implicitly in a level-set framework, by means of Monte-Carlo integration is proposed. The gra

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12

Bai, Xue. "Robust linear regression." Kansas State University, 2012. http://hdl.handle.net/2097/14977.

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Master of Science<br>Department of Statistics<br>Weixin Yao<br>In practice, when applying a statistical method it often occurs that some observations deviate from the usual model assumptions. Least-squares (LS) estimators are very sensitive to outliers. Even one single atypical value may have a large effect on the regression parameter estimates. The goal of robust regression is to develop methods that are resistant to the possibility that one or several unknown outliers may occur anywhere in the data. In this paper, we review various robust regression methods including: M-estimate, LMS estimat

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13

Guo, Mengmeng. "Generalized quantile regression." Doctoral thesis, Humboldt-Universität zu Berlin, Wirtschaftswissenschaftliche Fakultät, 2012. http://dx.doi.org/10.18452/16569.

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Die generalisierte Quantilregression, einschließlich der Sonderfälle bedingter Quantile und Expektile, ist insbesondere dann eine nützliche Alternative zum bedingten Mittel bei der Charakterisierung einer bedingten Wahrscheinlichkeitsverteilung, wenn das Hauptinteresse in den Tails der Verteilung liegt. Wir bezeichnen mit v_n(x) den Kerndichteschätzer der Expektilkurve und zeigen die stark gleichmßige Konsistenzrate von v-n(x) unter allgemeinen Bedingungen. Unter Zuhilfenahme von Extremwerttheorie und starken Approximationen der empirischen Prozesse betrachten wir die asymptotischen max

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14

GuÌˆnduÌˆz, Necla. "D-optimal designs for weighted linear regression and binary regression models." Thesis, University of Glasgow, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.301629.

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15

Song, Dogyoon. "Blind regression : nonparametric regression for latent variable models via collaborative filtering." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/105958.

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Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages 77-81).<br>Recommender systems are tools that provide suggestions for items that are most likely to be of interest to a particular user; they are central to various decision making processes so that recommender systems have bec

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16

Li, Ying. "A Comparison Study of Principle Component Regression, Partial Least Square Regression and Ridge Regression with Application to FTIR Data." Thesis, Uppsala University, Department of Statistics, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-127983.

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<p>Least squares estimator may fail when the number of explanatory vari-able is relatively large in comparison to the sample or if the variablesare almost collinear. In such a situation, principle component regres-sion, partial least squares regression and ridge regression are oftenproposed methods and widely used in many practical data analysis,especially in chemometrics. They provide biased coecient estima-tors with the relatively smaller variation than the variance of the leastsquares estimator. In this paper, a brief literature review of PCR,PLS and RR is made from a theoretical perspectiv

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17

Rosa, Lidiane Maria Ferraz. "Probabilidade do alarme falso no gráfico de controle EWMA para o monitoramento de processo autocorrelacionado." Universidade Federal de Viçosa, 2012. http://locus.ufv.br/handle/123456789/4057.

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Made available in DSpace on 2015-03-26T13:32:16Z (GMT). No. of bitstreams: 1 texto completo.pdf: 540189 bytes, checksum: 0753831535740967a377e10eb2b9b68d (MD5) Previous issue date: 2012-07-24<br>This work aimed to estimate the probability of false alarm caused by the control graph of the exponentially weighted moving average (EWMA) in an autocorrelated process along rational subgroups, using different combinations of the values of the following terms: number of standard deviations (2 ≤ k ≤ 6), weight of the rational subgroup (0.01 ≤ λ ≤ 1) and first order correla

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18

Salanti, Georgia. "The Isotonic Regression Framework." Diss., lmu, 2003. http://nbn-resolving.de/urn:nbn:de:bvb:19-9665.

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19

Nordvall, Andreas. "Agile regression system testing." Thesis, KTH, Data- och elektroteknik, 2012. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-102934.

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This report describes the work on automating the testing of nodes at CCS (Common Control System) in Ericsson. The goal was to every three hours configure nodes with the latest build and run the tests. This process is to be fully automatic without user in-put. The existing configuration tool CICC (Core Integration node Control Center) is to be used for configuration. Before work started fault reports were analyzed and creating a usecase for testing restarts should reduce some faults.The first step was to make the configuration tool CICC automated. To schedule the test-ing the continuous integra

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20

Pedroso, Estevam de Souza Camila. "Switching nonparametric regression models." Thesis, University of British Columbia, 2013. http://hdl.handle.net/2429/45130.

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In this thesis, we propose a methodology to analyze data arising from a curve that, over its domain, switches among J states. We consider a sequence of response variables, where each response y depends on a covariate x according to an unobserved state z, also called a hidden or latent state. The states form a stochastic process and their possible values are j=1,...,J. If z equals j the expected response of y is one of J unknown smooth functions evaluated at x. We call this model a switching nonparametric regression model. In a Bayesian switching nonparametric regression model the uncertainty a

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21

Yu, Keming. "Smooth regression quantile estimation." Thesis, Open University, 1996. http://oro.open.ac.uk/57655/.

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In this thesis, attention will be mainly focused on the local linear kernel regression quantile estimation. Different estimators within this class have been proposed, developed asymptotically and applied to real applications. I include algorithmdesign and selection of smoothing parameters. Chapter 2 studies two estimators, first a single-kernel estimator based on "check function" and a bandwidth selection rule is proposed based on the asymptotic MSE of this estimator. Second a recursive double-kernel estimator which extends Fan et al's (1996) density estimator, and two algorithms are given for

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22

SAMPAIO, ANTONIO JOSE CORREIA. "FUZZY LINEAR REGRESSIVE MODELS." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 1998. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=7440@1.

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CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>Este trabalho apresenta um modelo de Regressão Linear Nebulosa por Partes(RLNP). Trata-se de uma estrutura que envolve modelos de regressão linear por partes ponderadas por pertinências advindas da lógica nebulosa. Este modelo é comparado com o modelo de regressão linear. Os resultados mostram que o RLNP consegue identificar a estrutura não-linear dos dados simulados e que na maioria dos casos ele possui bom poder de ajuste.<br>In this dissertation a Fuzzy Piece-Wise Linear Regressive model FPLieR is developed. The model´

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23

Cribari-Neto, Francisco, and Achim Zeileis. "Beta Regression in R." Department of Statistics and Mathematics x, WU Vienna University of Economics and Business, 2009. http://epub.wu.ac.at/726/1/document.pdf.

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The class of beta regression models is commonly used by practitioners to model variables that assume values in the standard unit interval (0, 1). It is based on the assumption that the dependent variable is beta-distributed and that its mean is related to a set of regressors through a linear predictor with unknown coefficients and a link function. The model also includes a precision parameter which may be constant or depend on a (potentially different) set of regressors through a link function as well. This approach naturally incorporates features such as heteroskedasticity or skewness which a

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24

Bailey, Jacob. "Illinois basis regression models." Thesis, Kansas State University, 2014. http://hdl.handle.net/2097/17396.

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Master of Agribusiness<br>Department of Agricultural Economics<br>Sean Fox<br>The commodity markets have seen a great deal of volatility over the past decade, which, for those involved, has created many challenges and opportunities. Some of those challenges and opportunities are related to the behavior of the basis – the difference between the local cash price of grain and its price in the futures market. This thesis examines factors impacting basis for corn and soybeans at an Illinois River barge terminal, inland grain terminals in central Illinois, and in the Decatur processing market. Fa

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Nottingham, Quinton J. "Model-robust quantal regression." Diss., Virginia Tech, 1995. http://hdl.handle.net/10919/40225.

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Mitchell, Napoleon. "Outliers and Regression Models." Thesis, University of North Texas, 1992. https://digital.library.unt.edu/ark:/67531/metadc279029/.

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The mitigation of outliers serves to increase the strength of a relationship between variables. This study defined outliers in three different ways and used five regression procedures to describe the effects of outliers on 50 data sets. This study also examined the relationship among the shape of the distribution, skewness, and outliers.

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Robinson, Timothy J. "Dual Model Robust Regression." Diss., Virginia Tech, 1997. http://hdl.handle.net/10919/11244.

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In typical normal theory regression, the assumption of homogeneity of variances is often not appropriate. Instead of treating the variances as a nuisance and transforming away the heterogeneity, the structure of the variances may be of interest and it is desirable to model the variances. Aitkin (1987) proposes a parametric dual model in which a log linear dependence of the variances on a set of explanatory variables is assumed. Aitkin's parametric approach is an iterative one providing estimates for the parameters in the mean and variance models through joint maximum likelihood. Est

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28

Ehlers, Lathan. "REGRESSION TOWARD THE MEAN." OpenSIUC, 2017. https://opensiuc.lib.siu.edu/theses/2093.

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AN ABSTRACT OF THE THESIS OF Lathan Ehlers, for the Master of Fine Arts degree in Creative Writing, presented on 03 April 2017, at Southern Illinois University Carbondale. TITLE: REGRESSION TOWARD THE MEAN MAJOR PROFESSOR: Judy Jordan The poems in Regression Toward the Mean strive to determine a way to navigate the self when memory cannot be trusted. Understanding that memory is fallible, suggestible, and likely inaccurate, the speaker in these poems attempts find objective answers to questions surrounding his past by blending scientific theory with the personal narrative. Science and poet

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29

Rizzolo, Gregory. "The critique of regression." Thesis, University of Essex, 2018. http://repository.essex.ac.uk/21875/.

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When we dream, Freud (1900) maintained, we slip backwards from a world of conscious action to an unconscious realm of infantile memory and desire. The residues of our waking life meet there with repressed primitive wishes capable of animating a dream. The idea of regression, with all of its intrigue, would shape a century of theory building. It would also become one of the thorniest, if recently neglected, areas of inquiry. The history of the concept attests to two interwoven but distinct traditions. One tradition emphasizes the defensive, or evasive, function of regression. The other calls at

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30

Hirsch, Daniel, and Tim Steinholtz. "Tidsserie regression på finansmarknaden." Thesis, KTH, Skolan för teknikvetenskap (SCI), 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-255797.

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I den här rapporten studerar vi prestanda för två maskininlärningsalgoritmer när de implementeras för prisförutsättningar på den svenska elmarknaden. Målet med detta projekt är att utvärdera om dessa algoritmer kan användas som verktyg för investeringar. Algoritmerna är Kernel Ridge Regression (KRR) och Support Vector Regression (SVR). Både KRR och SVR använder kernel trick för att effektivt hitta olinjära beroende på den volatila marknaden. Metoderna används båda med ett offline-tillvägagångssätt. För Kernel Ridge Regression, genomfördes också en online-approach using Stochastic Gradient Desc

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31

Chen, Kun. "Regularized multivariate stochastic regression." Diss., University of Iowa, 2011. https://ir.uiowa.edu/etd/1209.

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In many high dimensional problems, the dependence structure among the variables can be quite complex. An appropriate use of the regularization techniques coupled with other classical statistical methods can often improve estimation and prediction accuracy and facilitate model interpretation, by seeking a parsimonious model representation that involves only the subset of revelent variables. We propose two regularized stochastic regression approaches, for efficiently estimating certain sparse dependence structure in the data. We first consider a multivariate regression setting, in which the larg

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32

Freitas, Margareth de Souza. "Derivação regressiva na perspectiva do modelo Dressler." [s.n.], 2010. http://hdl.handle.net/1884/24359.

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Zhang, Y. "Quantification of prediction uncertainty for principal components regression and partial least squares regression." Thesis, University College London (University of London), 2014. http://discovery.ucl.ac.uk/1433990/.

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Principal components regression (PCR) and partial least squares regression (PLS) are widely used in multivariate calibration in the fields of chemometrics, econometrics, social science and so forth, serving as alternative solutions to the problems which arise in ordinary least squares regression when explanatory variables are either collinear, or there are hundreds of explanatory variables with a relatively small sample size. Both PCR and PLS tackle the problems by constructing lower dimensional factors based on the explanatory variables. The extra step of factor construction makes the standar

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34

Dai, Elin, and Lara Güleryüz. "Factors that influence condominium pricing in Stockholm: A regression analysis : A regression analysis." Thesis, KTH, Matematisk statistik, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-254235.

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This thesis aims to examine which factors that are of significance when forecasting the selling price of condominiums in Stockholm city. Through the use of multiple linear regression, response variable transformation, and a multitude of methods for refining the model fit, a conclusive, out of sample validated model with a confidence level of 95% was obtained. To conduct the statistical methods, the software R was used. This study is limited to the districts of inner city Stockholm with the postal codes 112-118, and the final model can only be applied to this area as the postal codes are includ

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35

Chaves, Silvia Fernandes. "Ações regressivas: o cabimento e a crítica de uma interpretação civil do Direito Previdenciário." Pontifícia Universidade Católica de São Paulo, 2017. https://tede2.pucsp.br/handle/handle/19816.

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Submitted by Filipe dos Santos (fsantos@pucsp.br) on 2017-03-21T12:44:23Z No. of bitstreams: 1 Silvia Fernandes Chaves.pdf: 2018216 bytes, checksum: 04e85e9ece914fa42681b4d350e0c507 (MD5)<br>Made available in DSpace on 2017-03-21T12:44:23Z (GMT). No. of bitstreams: 1 Silvia Fernandes Chaves.pdf: 2018216 bytes, checksum: 04e85e9ece914fa42681b4d350e0c507 (MD5) Previous issue date: 2017-03-06<br>Conselho Nacional de Pesquisa e Desenvolvimento Científico e Tecnológico - CNPq<br>This thesis deals with the regressive actions provided for in Article 120 of Law N. 8.213/91, as well as new regres

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Chen, Hong Rui, and 陳弘叡. "Nonparametric Principal Components Regression Compared with Forward Regression." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/90471961665828545025.

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碩士<br>國立政治大學<br>統計學系<br>104<br>In a general linear regression model, when the sample size $n$ is greater than the number of variables $p$, it is common to use the least squares method to estimate the parameters in the regression model. When $n<p$, the parameters in the regression model cannot be estimated due to collinearity, so it is necessary to perform variable selection before estimating the parameters. In this thesis, I compare two variable selection methods in nonparametric additive regression. The first method is based on principal component analysis (PCA), and the second method is

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"Supervised ridge regression in high dimensional linear regression." 2013. http://library.cuhk.edu.hk/record=b5549319.

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在機器學習領域，我們通常有很多的特徵變量，以確定一些回應變量的行為。例如在基因測試問題，我們有數以萬計的基因用來作為特徵變量，而它們與某些疾病的關係需要被確定。沒有提供具體的知識，最簡單和基本的方法來模擬這種問題會是一個線性的模型。有很多現成的方法來解決線性回歸問題，像傳統的普通最小二乘回歸法，嶺回歸和套索回歸。設 N 為樣本數和，p 為特徵變量數，在普通的情況下，我們通常有足夠的樣本（N> P）。在這種情況下，普通線性回歸的方法，例如嶺回歸通常會給予合理的對未來的回應變量測值的預測。隨著現代統計學的發展，我們經常會遇到高維問題（N << P），如 DNA 芯片數據的測試問題。在這些類型的高維問題中，確定特徵變量和回應變量之間的關係在沒有任何進一步的假設的情況下是相當困難的。在很多現實問題中，儘管有大量的特徵變量存在，但是完全有可能只有極少數的特徵變量和回應變量有直接關係，而大部分其他的特徵變量都是無效的。套索和嶺回歸等傳統線性回歸在高維問題中有其局限性。套索回歸在應用於高維問題時，會因為測量噪聲的存在而表現得很糟糕，這將導致非常低的預測準確率。嶺回歸也有其明顯的局限性。它不能夠分開真正的特徵變量和無效的特徵變量。我提出的新方法的目的就是在高維線性回歸中克服以上兩種方法的局限性，從而導致更精確和穩定的預測。想法其實很簡單，與其做一個單一步驟的線性回歸，我們將回歸過程分成兩個步驟

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Yao, Ruji. "Regression trees." 1994. http://catalog.hathitrust.org/api/volumes/oclc/31260152.html.

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Liu, Su-Yun, and 劉素韻. "Robust Regression." Thesis, 2002. http://ndltd.ncl.edu.tw/handle/10070115676093643599.

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Huang, Shui-mei, and 黃秀梅. "quantile regression." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/59580896304481039057.

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WEN, YU-TING, and 溫俞婷. "Interaction Regression." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/32531082138760802618.

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碩士<br>國立交通大學<br>統計學研究所<br>103<br>The insertion of product terms into analytical model to test for presence of interaction effect is very common in economic, social and health sciences has two disadvantages: First, it has long been criticized for that existence of interaction is model dependent (Greenland (2009) and Mauderly and Samet (2009)). Second, this classical concept for interaction effect measurement shares the unawareness in common effect identification (Baron and Kenny (1986)) measuring the influences of explanatory variables only on regression function’s slope parameters ignoring its

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Mimno, David. "Topic regression." 2011. https://scholarworks.umass.edu/dissertations/AAI3498404.

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Text documents are generally accompanied by non-textual information, such as authors, dates, publication sources, and, increasingly, automatically recognized named entities. Work in text analysis has often involved predicting these non-text values based on text data for tasks such as document classification and author identification. This thesis considers the opposite problem: predicting the textual content of documents based on non-text data. In this work I study several regression-based methods for estimating the influence of specific metadata elements in determining the content of text docu

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Mimno, David. "Topic Regression." 2012. https://scholarworks.umass.edu/open_access_dissertations/520.

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Text documents are generally accompanied by non-textual information, such as authors, dates, publication sources, and, increasingly, automatically recognized named entities. Work in text analysis has often involved predicting these non-text values based on text data for tasks such as document classification and author identification. This thesis considers the opposite problem: predicting the textual content of documents based on non-text data. In this work I study several regression-based methods for estimating the influence of specific metadata elements in determining the content of text docu

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Tai, Yun Chiang, and 戴允強. "New Algorithms for Monotone Nonparametric Regression and Monotone Quantile Regression." Thesis, 2000. http://ndltd.ncl.edu.tw/handle/57201176596846154809.

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碩士<br>國立交通大學<br>統計所<br>88<br>A monotone nonparametric regression model is considered and a constrained weighted least squares solution is proposed for estimating monotone smooth functions from noisy data.The estimate obtained guarantees the monotonicity requirement.An efficient algorithm for computing the proposed solution is developed based on Lemke's algorithm for solving linear complemetarity problems.The leave-one-out cross validation method was adopted for the bandwidth selection.In addition,we propose a monotone nonparametric quantile regression method for interval estimation of the mean

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Cai, Deng. "Spectral Regression : a regression framework for efficient regularized subspace learning /." 2009. http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3362740.

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Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2009.<br>Source: Dissertation Abstracts International, Volume: 70-06, Section: B, page: 3593. Adviser: Jiawei Han. Includes bibliographical references (leaves 93-99) Available on microfilm from Pro Quest Information and Learning.

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Sayre, Kent. "Regression testing experiments." Thesis, 1999. http://hdl.handle.net/1957/33192.

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Software maintenance is an expensive part of the software lifecycle: estimates put its cost at up to two-thirds of the entire cost of software. Regression testing, which tests software after it has been modified to help assess and increase its reliability, is responsible for a large part of this cost. Thus, making regression testing more efficient and effective is worthwhile. This thesis performs two experiments with regression testing techniques. The first experiment involves two regression test selection techniques, Dejavu and Pythia. These techniques select a subset of tests from the origin

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林貞佑. "Regression Mode Interval." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/98044396995239762216.

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Lo, Yi, and 羅驛. "Weighted Quantile Regression." Thesis, 2010. http://ndltd.ncl.edu.tw/handle/31421059248782021412.

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Kao, Tzu-Yuan, and 高子瑗. "Effect Regression Analysis." Thesis, 2015. http://ndltd.ncl.edu.tw/handle/05416517583972590707.

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碩士<br>國立交通大學<br>統計學研究所<br>103<br>Specification of direct and total effects have been mistreated for years that will mislead to incorrect conclusion about statistical inferences about indirect effect. We prove that for detection of presence of mediation, it requires only to test the association between the predictor and mediator giving the reason that how Baron and Kenny (1986)’s three steps of tests has low power. We also provide theoretical proofs for the observation of Hayes (2009) for absence of total effect but there is indirect effect and the observation of Palmatier et al. (2009) for t

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Chen, Shing-Jin, and 陳興進. "Multivariate Regression Splines." Thesis, 1999. http://ndltd.ncl.edu.tw/handle/95792784455382660398.

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碩士<br>國立交通大學<br>統計所<br>87<br>A multivariate spline of nonuniform smoothness condition is introduced and a multivariate B-spline basis of local support is developed for this spline space. Simulation results for these splines are provided.

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