Sökning: "nonparametric models"
Visar resultat 1 - 5 av 36 avhandlingar innehållade orden nonparametric models.
1. Probabilistic Sequence Models with Speech and Language Applications
Sammanfattning : Series data, sequences of measured values, are ubiquitous. Whenever observations are made along a path in space or time, a data sequence results. To comprehend nature and shape it to our will, or to make informed decisions based on what we know, we need methods to make sense of such data. LÄS MER
2. Development and Evaluation of Nonparametric Mixed Effects Models
Sammanfattning : A nonparametric population approach is now accessible to a more comprehensive network of modelers given its recent implementation into the popular NONMEM application, previously limited in scope by standard parametric approaches for the analysis of pharmacokinetic and pharmacodynamic data. The aim of this thesis was to assess the relative merits and downsides of nonparametric models in a nonlinear mixed effects framework in comparison with a set of parametric models developed in NONMEM based on real datasets and when applied to simple experimental settings, and to develop new diagnostic tools adapted to nonparametric models. LÄS MER
3. Linear Models of Nonlinear Systems
Sammanfattning : Linear time-invariant approximations of nonlinear systems are used in many applications and can be obtained in several ways. For example, using system identification and the prediction-error method, it is always possible to estimate a linear model without considering the fact that the input and output measurements in many cases come from a nonlinear system. LÄS MER
4. Pointwise and Genomewide Significance Calculations in Gene Mapping through Nonparametric Linkage Analysis: Theory, Algorithms and Applications
Sammanfattning : In linkage analysis or, in a wider sense, gene mapping one searches for disease loci along a genome. This is done by observing so called marker genotypes (alleles) and phenotypes (affecteds/unaffecteds) of a pedigree set, i.e. LÄS MER
5. Data Driven Visual Recognition
Sammanfattning : This thesis is mostly about supervised visual recognition problems. Based on a general definition of categories, the contents are divided into two parts: one which models categories and one which is not category based. We are interested in data driven solutions for both kinds of problems. LÄS MER