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Model Selection and Model Averaging [PDF]
, 2015 info:eu-repo/semantics ...
Claeskens, Gerda, Jansen, Maarten
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Model Selection For Geostatistical Models
Ecological Applications, 2006We consider the problem of model selection for geospatial data. Spatial correlation is often ignored in the selection of explanatory variables, and this can influence model selection results. For example, the importance of particular explanatory variables may not be apparent when spatial correlation is ignored.
Jennifer A, Hoeting +3 more
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In favor of the selective model of positive selection
Seminars in Immunology, 1994The mechanisms of thymocyte commitment towards the CD4+ and CD8+ lineage remain unresolved. Two models--one based on instruction, the other on selection--have previously been proposed. The instructional model has been popularly received based on results of earlier studies.
Chan, Susan +2 more
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Attribute selection for modelling
Future Generation Computer Systems, 1997Abstract Modelling a target attribute by other attributes in the data is perhaps the most traditional data mining task. When there are many attributes in the data, one needs to know which of the attribute(s) are relevant for modelling the target, either as a group or the one feature that is most appropriate to select within the model construction ...
Igor Kononenko 0001, Se June Hong
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Statistical Methods & Applications, 2016
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Umberto Amato +2 more
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zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Umberto Amato +2 more
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Theoretical Population Biology, 1974
Abstract Neglecting age-structure, but taking into account matings with differential fertility in Mendelian reproduction, continuous selective models are formulated for a single locus with an arbitrary number of alleles, with or without distinguishing the sexes, and for two alleles at each of two loci in a monoecious population. In each case, without
Nagylaki, Thomas, Crow, James F.
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Abstract Neglecting age-structure, but taking into account matings with differential fertility in Mendelian reproduction, continuous selective models are formulated for a single locus with an arbitrary number of alleles, with or without distinguishing the sexes, and for two alleles at each of two loci in a monoecious population. In each case, without
Nagylaki, Thomas, Crow, James F.
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Model Validation for Model Selection
2001Gaussian mixture modelling is used to provide a semi-parametric density description for a given data set. The fundamental problem with this approach is that the number of mixtures required to adequately describe the data is not known in advance. In our previous work [12] we introduced a new concept, termed Predictive Validation as a basis for an ...
Josef Kittler +2 more
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IEEE Transactions on Systems, Man, and Cybernetics, 1995
Complex systems such as computers, aerospace systems, etc., are often tested by using a sequence of tests to exercise the functionality of the system. If the system fails a test, an error message is generated, initiating the test selection (TS) phase. The troubleshooter must decide whether or not to run more tests.
Inderpal S. Bhandari +2 more
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Complex systems such as computers, aerospace systems, etc., are often tested by using a sequence of tests to exercise the functionality of the system. If the system fails a test, an error message is generated, initiating the test selection (TS) phase. The troubleshooter must decide whether or not to run more tests.
Inderpal S. Bhandari +2 more
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1994
Fitting data by a certain generalized linear model means choosing appropriate forms for the predictor, the link function, and the exponential family or variance function. In the previous chapters Pearsons’s X 2, the deviance and, in the multinomial case, the power-divergence family were introduced as general goodness-of-fit statistics.
Ludwig Fahrmeir, Gerhard Tutz
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Fitting data by a certain generalized linear model means choosing appropriate forms for the predictor, the link function, and the exponential family or variance function. In the previous chapters Pearsons’s X 2, the deviance and, in the multinomial case, the power-divergence family were introduced as general goodness-of-fit statistics.
Ludwig Fahrmeir, Gerhard Tutz
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