Prognostic Models for Remission – Mixture Modelling
Comparison of single distribution and mixture distribution models for modelling LGD
... default). Modelling PD, the probability of default has been the objective of credit scoring systems for fifty years but modelling LGD is not something that had really been addressed in consumer credit until ...
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Mixture Modelling Approach
... This paper has investigated changes in life satisfaction across the retirement transition using Latent Growth Mixture Modelling. It found that there are distinct phases of change in life satisfaction ...
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Prognostic modelling of breast cancer patients: a benchmark of predictive models with external validation
... the prognostic index obtained with a prognostic model, which was in this study, either with Cox or PLANN-ARD, and one or more predictor ...a mixture of continuous and categorical ...
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Prognostic Models in Dengue
... Multivariable analysis Linearity and additivity assessments As shown in Table 4.5, flexible spline functions showed a significant improvement for modelling the day of illness and HCT while linear terms seemed to ...
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Mixture Models and Convergence Clubs
... Mixture Models and Convergence Clubs Maria Grazia Pittau ∗ Roberto Zelli † Paul ...that modelling the cross-country distribution of per capita income as a mixture distribution provides a ...
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Topic-based mixture language modelling
... This paper investigates topic-based mixture language processing using IR statisti- cal models. Three term weighting schemes are examined (raw unigram frequencies, Okapi and entropy-based), and for each ...
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Mixture Modelling of the HEXACO Personality Inventory
... it models the equivalent of a main effect where participants in one profile tend to get higher scores on all ...of mixture modeling is the Facet by Profile interaction, also referred to as Shape, which in ...
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Challenges in modelling the random structure correctly in growth mixture models and the impact this has on model mixtures
... growth mixture models (GMMs) to estimate such ...constrained models with and without an autocorrelation structure to assess the impact this had on the ideal number of latent classes, their size and ...
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Modelling asset return using multivariate asymmetric mixture models with applications to estimation of Value-at-Risk
... for modelling asset ...competing models in this ...restrictive models (the FM-MN, FM-MSN and FM-MSAL models) have fitted a two-component mixture model in order to accommodate the ...
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Spatial–temporal modelling of fMRI data through spatially regularized mixture of hidden process models
... In model-based fMRI analysis, the inference of temporal fMRI models can be rather complex as the temporal resolution of fMRI data is typically low. Therefore, temporal constraints are usually imposed. The ...
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VoIP Traffic Modelling using Gaussian Mixture Models, Gaussian Processes and Interactive Particle Algorithms
... 3 MIXvoip S.a., Z.I. Rohlach, Sandweiler, Luxembourg Email: [email protected] Abstract—The paper deals with an important problem in the Voice over IP (VoIP) domain, namely being able to understand and predict the ...
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A Bayesian mixture modelling approach for spatial proteomics.
... Gaussian mixture models, for spatial proteomics can provide whole sub-cellular proteome uncertainty quantification on the assignment of proteins to organelles and such information is ...
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Computational information geometry in statistics: mixture modelling
... of mixture modelling. A mixture model is a discrete or continuous convex combination of distributions from a pre-specified (often, exponential) family: f (y; Q) = R ...Such models arise ...
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Randomised mixture models for pricing kernels
... particular mixture of those, and the pricing kernel model jointly characterize the dynamics of the derived interest rate ...for modelling interest rates for long time ...particular mixture of ...
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Bayesian mixture models for count data
... process mixture of regression models where the mixing weights vary with ...flexible modelling of the response variable Y given the covariates X = ...regression models the probability den- sity ...
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Prediction with Mixture Models
... 5. Conclusion and Discussion The identification of spam-disseminating botnets can be reduced to the problem of clustering the graph of email messages in which messages are linked if they originate from the same IP ...
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Finite Mixture Models
... It is known that female halibut is longer, on average, than male …sh and that the distribution of lengths is normal. Gender cannot be determined at measurement[r] ...
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Mixture of normals probit models
... the mixture these models effectively remove the normality assumption and are much closer to semiparametric ...favor mixture of normals probit models over the conventional probit model, and the ...
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Estimation of Finite Mixture Models
... class is the most accurate. The set theoretic estimates guarantee that a solution will satisfy the finite mixture model set as well as the sum-to-one and nonnegativity constraints. The SPOCS estimate is not affected ...
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On learning mixture models for permutations
... a mixture of distributions on permutations where each distribution in the mixture generated by a Mallows model, with its own center and ...the mixture can be learned? We show that for learnability, ...
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