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 354 for “"Ordinal"”.
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ORDINAL
… behind you and you are no longer being observed. Ordinal is an exploration of obscene consumption. The images and words consumed can be understood to symbolize the consumption of the body. This piece may register as significant of a sexual act or acts, but is intended to be understood as solitary, …
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ORDINAL
… behind you and you are no longer being observed. Ordinal is an exploration of obscene consumption. The images and words consumed can be understood to symbolize the consumption of the body. This piece may register as significant of a sexual act or acts, but is intended to be understood as solitary, …
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Ordinal HyperPlane Loss
… analyzing ordered class data, commonly called “ordinal class” data. The focus of the work is the development of classifiers (predictive models) that predict classes from available data. Ratings scales, medical classification scales, socio-economic scales, meaningful groupings of continuous data, …
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Transfinite Ordinal Arithmetic
… times, an arithmetic of finite and transfinite ordinal numbers is outlined. The concept of a set is outlined and directed to the understanding that an ordinal, a special kind of number, is a particular kind of well-ordered set. From this, the idea of counting ordinals is introduced. With the …
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Hyperarithmetical Functions of Ordinal Numbers
Made available in DSpace on 2014-12-09T22:17:35Z (GMT). No. of bitstreams: 1 6706674.pdf: 1481875 bytes, checksum: 8a50fea5076bb690649350539813f6e9 (MD5) Previous issue date: 1966
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Collaborative ranking from ordinal data
… techniques. Recent studies have shown that ordinal (comparison) data can outperform cardinal data in learning preferences, but there has not been much study on learning personalized preferences from ordinal data. This thesis presents a matrix factorization inspired, convex relaxation …
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Conditional Quantile Estimation With Ordinal Data
… to the analysis of the relation between an ordinal response variable and a set of covariates and propose a new regression method for estimating the conditional quantiles of the ordinal response variable. By assuming a continuous latent variable underlying the observed ordinal response …
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Comparing Dependent Correlations for Ordinal Data
… and application for analyzing categorical ordinal data have matured in statistical inferences during recent decades of development. The methods include logistic regression models, odds ratios, inferential methods by using chi-squared tests of independence and conditional independence. On …
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Initial segments in ordinal recursion theory.
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mathematics, 1979
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The analysis of longitudinal ordinal data
… quantal responses. Special emphasis is placed on ordinal and binary data because of their prevalence in ecological, biological, and environmental statistics. The first chapters review the literature and introduce necessary theory. The second part of this dissertation consists of a case study in …
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Modeling and Measuring Association for Ordinal Data
… estimator of common odds ratio in a K x K ordinal contingency table where the category numbers of the variables are the same. The M[superscript2] statistic with scoring systems is also introduced. From the simulation results, we figure out that the chi-square statistics do not work except …
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Essays on the econometrics of ordinal data
In economics, ordinal variables like general health, mental health, and happiness level play a crucial role. Ordinal data is commonly used in surveys and questionnaires due to its ordered structure. However, incorporating an ordinal outcome variable in economic studies presents challenges. The …
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Ordinal Regression to Evaluate Student Ratings Data
… from Fall 2001 to Fall 2006. This project uses ordinal regression to model the probability of an instructor receiving a good, average, or poor rating. Student grade, instructor status, class level, student gender, total enrollment, term, GE class status, and college are used as explanatory …
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Bayesian Multidimensional Scaling Model for Ordinal Preference Data
… to interpret two independent data samples of ordinal consumer preference data related to purchasing behavior. The objective of the procedure was to provide an understanding and visual depiction of consumers' likelihood of having a strong affinity toward one of the survey choices, and how other …
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Modeling Correlated Ordinal Data: Marginal and Conditional Approaches
General computing algorithms are developed in R for the GEE computations and WinBugs to perform Gibbs sampling for the Bayesian analysis. Analyses of randomized controlled longitudinal data and randomized controlled surgical data are used to illustrate the features of the class of models.
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Unified Ordinal Regression: Model Assessment and Semiparametric Analysis
… squares algorithm for cumulative link models for ordinal responses.
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Applying Bayesian Ordinal Regression to ICAP Maladaptive Behavior Subscales
This paper develops a Bayesian ordinal regression model for the maladaptive subscales of the Inventory for Client and Agency Planning (ICAP). Because the maladaptive behavior section of the ICAP contains ordinal data, current analysis strategies combine all the subscales into three indices, making …
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The Perception of Ordinal Depth Relationship from Static and Deforming Boundary Contours
… 1999; Norman & Todd, 1996, 1998) before making ordinal depth judgments about two highlighted regions on the object's surface. Two local regions on the objects' surface were highlighted, and the observers were required to judge which of the two regions was closer to them in depth. In Experiment …
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Prediction of Conditional Quantiles in Ordinal Regression With Applications to Aging Research
Key words: Ordinal data; Quantile regression; Nonparametric transformation model; Second Longitudinal Study of Aging.
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