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.
Results
Showing 1 to 20 of 46 for “"discrete data"”.
-
Analysis of Discrete Data under Order Restrictions
Strategies for the analysis of discrete data under order restrictions are discussed. We consider inference for sequences of binomial populations, and the corresponding risk difference, relative risk and odds ratios. These concepts are extended to deal with independent multinomial populations. …
-
Statistical Analysis of Longitudinal and Multivariate Discrete Data
… equations, and illustrate it on two real life data sets. Next we study over and under dispersed models including quasi-multinomial and Lagrange families of distributions. We implement the maximum likelihood method for the quasi-multinomial model and illustrate the application of this model for …
-
Scalable Bayesian Matrix and Tensor Factorization for Discrete Data
… methods decompose the observed matrix and tensor data into a set of factor matrices. They provide a useful way to extract latent factors or features from complex data, and also to predict missing data. Matrix and tensor factorization has drawn significant attentions in a wide variety of …
-
Multilevel Latent Markov Models for Nested Longitudinal Discrete Data
Multilevel longitudinal data are clustered both structurally and temporally. The hierarchically nested structure induces between-subject dependency because individuals in the same unit may share something in common. The longitudinal aspect of data induces within-subject dependency because …
-
Pattern extraction and clustering for high-dimensional discrete data
… factorizations with interesting problems in data mining and machine learning. We propose a framework for solving several low-rank matrix factorization problems, including binary matrix factorization, constrained binary matrix factorization, weighted constrained binary matrix factorization, …
-
Probabilistic Modeling of Multi-relational and Multivariate Discrete Data
… knowledge from multi-relational and multivariate discrete data is a crucial task that arises in many research and application domains, e.g. text mining, intelligence analysis, epidemiology, social science, etc. In this dissertation, we study and address three problems involving the modeling of …
-
Optimum Design and Sensitivity of Discrete-Data Linear and Nonlinear Systems
Made available in DSpace on 2014-12-04T21:03:28Z (GMT). No. of bitstreams: 1 6202975.pdf: 3206993 bytes, checksum: 4bcb30f2bf8a5a42dffe637afb8f527c (MD5) Previous issue date: 1962
-
Extending the Information Partition Function: Modeling Interaction Effects in Highly Multivariate, Discrete Data
Because of the huge amounts of data made available by the technology boom in the late twentieth century, new methods are required to turn data into usable information. Much of this data is categorical in nature, which makes estimation difficult in highly multivariate settings. In this thesis we …
-
Large Scale Disease Modeling
… will include long distance travel. From this discrete data, we can then build an SIR model in the PDE sense to display large scale disease spread.</p>
-
Functional linear regression on Namibian and South African data
… such as the multivariate nature of the data. Functional data analysis was used in this project to display the data so as to highlight various characteristics while allowing us to study important sources of pattern and variation among the data. Functional data analysis can be best …
-
Algorithms for modeling and simulation of biological systems; applications to gene regulatory networks
… and proteomics have gathered a remarkable amount data enabling the possibility of a system-level analysis to be grounded at a molecular level. The reverse-engineering of biochemical networks from experimental data has become a central focus in systems biology. A variety of methods have been …
-
Observations and modelling of the variability of the Solent-Southampton Water estuarine system
… ocean. The combination of numerical models and discrete datasets is used to describe and investigate processes of natural variability in the partially-mixed, non-turbid, macrotidal Solent-Southampton Water estuarine system (UK).<br/>The estuarine circulation and the response of wind forcing is …
-
Absolute Frequency Data for Statistical Computing: A Comparison With Sample-Based Approaches and Guidelines for Improving Software Implementation
Data sets comprising a large number of discrete data points that include multiple repeated values can be expressed in absolute frequency form, which represents the data more compactly by listing the number of occurrences for each unique value present in the full data set. This form of data can …
-
Grounding for a computational model of place
… electronic decedents deconstruct places into discrete data and require user interpretation to reconstruct the original sense of place. Is it possible to create maps that preserve this sense of place and successfully communicate it to the user? This thesis presents a model, and an application …
-
The relationships between discrete and continuous probability distributions
Though some of the discrete distributions, for example the binomial, hypergeometric, Poisson, are well tabulated, often statisticians use the percentage points of approximating continuous distributions when analysing discrete data. In this thesis, the exact relationships between certain discrete …
-
Bayesian analysis for mixtures of discrete distributions with a non-parametric component
… smaller false non-discovery rate in the case of discrete data. Moreover, it does not incur the label-switching problem. An application of the method to data generated by ChIP-sequencing experiments is shown. A one-dimensional Markov random field model is proposed, which accounts for the spatial …
-
Anomaly detection methods for unmanned underwater vehicle performance data
… problem of detecting anomalies in performance data for unmanned underwater vehicles(UUVs). UUVs collect a tremendous amount of data, which operators are required to analyze between missions to determine if vehicle systems are functioning properly. Operators are typically under heavy time …
-
Towards an Information Theoretic Framework for Evolutionary Learning
… theoretic quantities on mixed continuous and discrete data via the empirical copula and information dimension. We extend statistical resampling. We present experimental and real world application results: chaotic time series prediction; parity; complex continuous functions; industrial process …
Page 1 of 3