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Physical Sciences and Mathematics Commons™
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- Acceleration techniques (1)
- Approximation theory (1)
- Cell proliferation (1)
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- Experimental design (1)
- Faulty measurements (1)
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- Non-homogeneous poisson process (NHPP) (1)
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- Software reliability (1)
- Structural optimization (1)
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Articles 1 - 6 of 6
Full-Text Articles in Physical Sciences and Mathematics
Detection Of Outliers And Influential Observations In Regression Models, Anwar M. Hossain
Detection Of Outliers And Influential Observations In Regression Models, Anwar M. Hossain
Mathematics & Statistics Theses & Dissertations
Observations arising from a linear regression model, lead one to believe that a particular observation or a set of observations are aberrant from the rest of the data. These may arise in several ways: for example, from incorrect or faulty measurements or by gross errors in either response or explanatory variables. Sometimes the model may inadequately describe the systematic structure of the data, or the data may be better analyzed in another scale. When diagnostics indicate the presence of anomalous data, then either these data are indeed unusual and hence helpful, or contaminated and, therefore, in need of modifications or …
Software Reliability Models, Syed Afzal Hossain
Software Reliability Models, Syed Afzal Hossain
Mathematics & Statistics Theses & Dissertations
The problem considered here is the building of Non-homogeneous Poisson Process (NHPP) model. Currently existing popular NHPP process models like Goel-Okumoto (G-O) and Yamada et al models suffer from the drawback that the probability density function of the inter-failure times is an improper density function. This is because the event no failure in (0, oo] is allowed in these models. In real life situations we cannot draw sample(s) from such a population and also none of the moments of inter-failure times exist. Therefore, these models are unsuitable for modelling real software error data. On the other hand if the density …
Best Approximation With Geometric Constraints, Yuesheng Xu
Best Approximation With Geometric Constraints, Yuesheng Xu
Mathematics & Statistics Theses & Dissertations
This is a study of best approximation with certain geometric constraints. Two major problem areas are considered: best Lp approximation to a function in Lp (0,1) by convex functions, (m, n)-convex functions, (m, n)-convex functions and (m, n)-convex splines, for 1 < p < ∞ , and best uniform approximation to a continuous function by convex functions, quasi-convex functions and piecewise monotone functions.
Mathematical Models Of Prevascular Tumor Growth By Diffusion, Sophia A. Maggelakis
Mathematical Models Of Prevascular Tumor Growth By Diffusion, Sophia A. Maggelakis
Mathematics & Statistics Theses & Dissertations
A study of several complementary mathematical models that describe the early, prevascular stages of solid tumor growth by diffusion under various simplifying assumptions is presented. The advantage of these models is that their degree of complexity is relatively low, which ensures fairly straightforward comparisons with experimental or clinical data (as it becomes available), yet they are mathematically sophisticated enough to capture the main biological phenomena of interest.
The tumor growth and cell proliferation rate are assumed to depend on the local concentrations of nutrients and inhibitory factors. The effects of geometry and spatially non-uniform inhibitor production and non-uniform nutrient consumption …
Optimal Row-Column Designs For Correlated Errors And Nested Row-Column Designs For Uncorrelated Errors, Nizam Uddin
Optimal Row-Column Designs For Correlated Errors And Nested Row-Column Designs For Uncorrelated Errors, Nizam Uddin
Mathematics & Statistics Theses & Dissertations
In this dissertation the design problems are considered in the row-column setting for second order autonormal errors when the treatment effects are estimated by generalized least squares, and in the nested row-column setting for uncorrelated errors when the treatment effects are estimated by ordinary least squares. In the former case, universal optimality conditions are derived separately for designs in the plane and on the torus using more general linear models than those considered elsewhere in the literature. Examples of universally optimum planar designs are given, and a method is developed for the construction of optimum and near optimum designs, that …
On Vector Sequence Transforms And Acceleration Techniques, Steven L. Hodge
On Vector Sequence Transforms And Acceleration Techniques, Steven L. Hodge
Mathematics & Statistics Theses & Dissertations
This dissertation is devoted to the acceleration of convergence of vector sequences. This means to produce a replacement sequence from the original sequence with higher rate of convergence.
It is assumed that the sequence is generated from a linear matrix iteration xi+ i = Gxi + k where G is an n x n square matrix and xI+1 , xi,and k are n x 1 vectors. Acceleration of convergence is obtained when we are able to resolve approximations to low dimension invariant subspaces of G which contain large components of the error. When …