Pages that link to "Item:Q4419458"

The following pages link to Model Selection and the Principle of Minimum Description Length (Q4419458):

Displaying 50 items.

• Posterior model consistency in variable selection as the model dimension grows (Q254450) (← links)
• Information optimality and Bayesian modelling (Q280206) (← links)
• Model selection criteria for a linear model to solve discrete ill-posed problems on the basis of singular decomposition and random projection (Q333589) (← links)
• Structure detection and parameter estimation for NARX models in a unified EM framework (Q445898) (← links)
• Boosting algorithms: regularization, prediction and model fitting (Q449780) (← links)
• Variable selection in linear regression: several approaches based on normalized maximum likelihood (Q553666) (← links)
• The flexibility of models of recognition memory: an analysis by the minimum-description length principle (Q654392) (← links)
• An extended minimum description length (MDL) penalty function for binomial proportions (Q713666) (← links)
• Estimation of structure by minimum description length (Q794965) (← links)
• The polyharmonic local sine transform: a new tool for local image analysis and synthesis without edge effect (Q818335) (← links)
• On the quantification of model uncertainty: a Bayesian perspective (Q823871) (← links)
• Scale-based Gaussian coverings: combining intra and inter mixture models in image segmentation (Q845422) (← links)
• Rival approaches to mathematical modelling in immunology (Q885912) (← links)
• Fitting of mixtures with unspecified number of components using cross validation distance estimate (Q951801) (← links)
• Model selection with the loss rank principle (Q962384) (← links)
• An MDL approach to the climate segmentation problem (Q977634) (← links)
• Feature selection for Bayesian network classifiers using the MDL-FS score (Q990984) (← links)
• A minimum description length approach to hidden Markov models with Poisson and Gaussian emissions. Application to order identification (Q1007478) (← links)
• Minimum message length shrinkage estimation (Q1017808) (← links)
• Knot selection by boosting techniques (Q1020124) (← links)
• MDL principle for robust vector quantisation (Q1294723) (← links)
• Generalized Levinson--Durbin and Burg algorithms. (Q1421316) (← links)
• Maximized log-likelihood updating and model selection. (Q1423127) (← links)
• Two-step sparse boosting for high-dimensional longitudinal data with varying coefficients (Q1615281) (← links)
• Prior distributions for objective Bayesian analysis (Q1631565) (← links)
• High-dimensional penalty selection via minimum description length principle (Q1631787) (← links)
• Hierarchical two-part MDL code for multinomial distributions (Q1726276) (← links)
• Efficient semiparametric estimation and model selection for multidimensional mixtures (Q1746537) (← links)
• Model uncertainty (Q1766316) (← links)
• Consistency of minimum description length model selection for piecewise stationary time series models (Q1951119) (← links)
• Model selection based on minimum description length (Q1977908) (← links)
• The minimum description length principle for pattern mining: a survey (Q2097441) (← links)
• A randomized method for solving discrete ill-posed problems (Q2263217) (← links)
• Model selection by sequentially normalized least squares (Q2267585) (← links)
• Multiple changepoint detection with partial information on changepoint times (Q2316608) (← links)
• On the computation of entropy prior complexity and marginal prior distribution for the Bernoulli model (Q2320933) (← links)
• Boosting as a kernel-based method (Q2331677) (← links)
• Description length and dimensionality reduction in functional data analysis (Q2361186) (← links)
• Early stopping in \(L_{2}\)Boosting (Q2445675) (← links)
• Constructing a speculative kernel machine for pattern classification (Q2488681) (← links)
• Accumulative prediction error and the selection of time series models (Q2507906) (← links)
• Model selection by normalized maximum likelihood (Q2507907) (← links)
• An empirical study of minimum description length model selection with infinite parametric complexity (Q2507908) (← links)
• Flexible scan statistic test to detect disease clusters in hierarchical trees (Q2512757) (← links)
• Model selection by minimum description length: lower-bound sample sizes for the Fisher information approximation (Q2513825) (← links)
• Wavelet-based gradient boosting (Q2631350) (← links)
• On the prevalence of information inconsistency in normal linear models (Q2666033) (← links)
• Minimum description length method for facet matching (Q2751992) (← links)
• Nonparametric Regression Based Image Analysis (Q2787370) (← links)
• Subset selection in linear regression using sequentially normalized least squares: asymptotic theory (Q2815586) (← links)