Displaying similar documents to “A selection modelling approach to analysing missing data of liver Cirrhosis patients”

Thermodynamics of DNA microarrays

Enrico Carlon (2008)

Banach Center Publications

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DNA microarrays have been widely used in molecular biology laboratories. The main current application of these devices is the determination of the gene expression level for thousands of genes simultaneously. Here we review a recently introduced physical model for hybridization (i.e. the binding of complementary DNA strands) in Affymetrix arrays and compare it to experimental results. The experimental data follow rather well the microscopic model and the approach offers several advantages...

Pattern-mixture models

Geert Molenberghs, Herbert Thijs, Bart Michiels, Geert Verbeke, Michael G. Kenward (2004)

Journal de la société française de statistique

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Survival analysis on data streams: Analyzing temporal events in dynamically changing environments

Ammar Shaker, Eyke Hüllermeier (2014)

International Journal of Applied Mathematics and Computer Science

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In this paper, we introduce a method for survival analysis on data streams. Survival analysis (also known as event history analysis) is an established statistical method for the study of temporal “events” or, more specifically, questions regarding the temporal distribution of the occurrence of events and their dependence on covariates of the data sources. To make this method applicable in the setting of data streams, we propose an adaptive variant of a model that is closely related to...

A model for credit scoring: an application of discriminant analysis.

Manuel Artís, Montserrat Guillén, José M.ª Martínez (1994)

Qüestiió

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The application of statistical techniques in decision making, and more specifically for classification requirements, has proved to be adequate in the context of financial problems. In this study, we present the methodology used and the results obtained in the elaboration of a decision-support system for credit assignment. The problem was to provide an automatic tool for a Spanish financial institution that needed to quantify and analyse credit applications from clients. Firstly, we shall...

Rough modeling - a bottom-up approach to model construction

Terje Loken, Jan Komorowski (2001)

International Journal of Applied Mathematics and Computer Science

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Traditional data mining methods based on rough set theory focus on extracting models which are good at classifying unseen obj-ects. If one wants to uncover new knowledge from the data, the model must have a high descriptive quality-it must describe the data set in a clear and concise manner, without sacrificing classification performance. Rough modeling, introduced by Kowalczyk (1998), is an approach which aims at providing models with good predictive emphand descriptive qualities, in...