Leuven, B-3000
Belgium
KU Leuven - Department of Economics
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Pay-as-you-drive insurance, Usage-based insurance, Risk classification, Generalized additive models, Compositional predictors, Structural zeros
Benchmarking; Credit risk modeling; Competing risks; Mixture cure model; Survival analysis
Error rate, Focussed information criterion, Forward selection, Logistic regression, Model selection, Risk measures
Causal inference, Confounder selection, Double robustness, Influential weights, Model selection, Model uncertainty, Propensity score
forecast combination, optimal weights, model selection
forecast combination, optimal weights
quantile regression, model selection focused information criterion
Mixed model, Best linear unbiased prediction, Bootstrap inference, Natural resource survey
Multivariate Erlang mixtures with a common scale parameter, Density estimation, Censored data, Truncated data, Expectation-maximization algorithm, Maximum likelihood.
Akaike information criterion, Bayes information criterion, Efficient semi-parametric estimation, Frequentist model averaging, Model averaging, Model selection, Profile likelihood, Semiparametric model
Gamma distribution, Goodness-of-fit, Frailty model, Order selection test, Orthogonal polynomials
gamma distribution, goodness-of-fit, frailty model, order selection test, orthogonal polynomials
Frequentist model averaging, mean squared error, weight choice, local misspecification, likelihood regression
Calibration, Generalized regression estimation, Nonparametric regression, Restricted maximum likelihood
mixed model, hypothesis test, nonparametric test, minimum distance, orderselection
mixed model, hypothesis test, nonparametric test, minimum distance, order selection
M-estimator, Penalized least squares method, Penalized regression
Akaike information criterion, conditional likelihood, effective degrees of freedom, mixed model, penalized regression spline, S-estimation
Classification, Criteria, Error rate, Information, Information criterion, IT, Model, Models, Performance, Problems, Selection, Simulation, Space, Studies, Supervised classification, Support vector machine, Variable selection
Akaike information criterion, Competing risks, EM-algorithm, Mixture cure model, Model selection.
Directed acyclic graph, Copula, C-vine, D-vine, Model selection
AIC, Akaike's information criterion, Criteria, Data, Information, Information criterion, Methods, Model, Model selection, Problems, Selection, Simulation, Studies, Variable selection, Work
Lack-off-fittest; Likelihood ratio test; Mixed models; One-sided test; Penalization; Restricted maximum likelihood; Variance components; Wavel; Asymptotic distribution; Distribution; Likelihood; Tests; Models; Model; Random effects; Effects; Studies; Lack-of-fit; Mixed model; Framework; Functions; D
Bayesian Inference, Functional data analysis, Markov chain Monte Carlo sampling,Bayesian Inference, Functional data analysis, Markov chain Monte Carlo sampling,
Bayesian penalized splines, B-splines, Confidence band, Mixed model, Penalization
statistical depth, functional data, time warping, multivariate data
Double exponential family, Extended Quasi-Likelihood, Modeling
variable selection, focused information criterion, penalized estimation, lasso, model averaging, efficiency, prediction loss
Akaike's information criterion, robust estimation, variable selection
fMRI connectivity, Focused information criterion, Model selection, Gaussian graphical model, Penalization, High-dimensional data
Regression, Problems, Lack-of-fit, Applications
Functional data, clustering, phase variation, amplitude variation, warping
Variable selection, Social network, Focused information criterion, Exponential random graphs, Network based models
Akaike information criterion, confidence region, likelihood model, model selection, post-selection inference
Focused information criterion, model selection, directed acyclic graph, Gaussian graphical model, ancestral graph
functional data, time warping, curve registration, adaptive MCMC, C, R
Desparsified estimator; Focused information criterion; High-dimensional data; Variable selection.
clustered data, copulas, model selection, multivariate data, right-censoring, survival data.
high-dimensional data, single-index model, regularized estimation, sparsity, asymptotic normality, confidence interval
Akaike information criterion, hypothesis test, multiple imputation, lack-of-fit test, missing data, omnibus test, order selection
Anisotropy, Besov spaces, minimax and maxiset approaches, linear and non linear methods, thresholding rules, multidimensional wavelet basis
Anisotropy, Besov spaces, information pooling, linear and non linear methods, multivariate wavelet basis, thresholding
anisotropy, hyperbolic wavelet basis, information pooling, maxiset, wavelet thresholding, atomic dimension
Model selection, Variable selection, Information criteria, Model averaging
