Pages that link to "Item:Q1977908"

The following pages link to Model selection based on minimum description length (Q1977908):

Displaying 38 items.

• The philosophy of Bayes factors and the quantification of statistical evidence (Q296918) (← links)
• Prior sensitivity in theory testing: an apologia for the Bayes factor (Q618178) (← links)
• Estimation of structure by minimum description length (Q794965) (← links)
• Cumulative prospect theory's functional menagerie (Q867443) (← links)
• Model selection with the loss rank principle (Q962384) (← links)
• On the minimum description length complexity of multinomial processing tree models (Q979181) (← links)
• Measurement by subjective estimation: Testing for separable representations (Q1023423) (← links)
• MDL principle for robust vector quantisation (Q1294723) (← links)
• Stochastic complexity and model selection from incomplete data (Q1298904) (← links)
• Avoiding the dangers of averaging across subjects when using multidimensional scaling. (Q1398360) (← links)
• Languages for gestalts of line patterns. (Q1410778) (← links)
• Maximized log-likelihood updating and model selection. (Q1423127) (← links)
• Assessing model mimicry using the parametric bootstrap. (Q1431814) (← links)
• High-dimensional penalty selection via minimum description length principle (Q1631787) (← links)
• Hierarchical two-part MDL code for multinomial distributions (Q1726276) (← links)
• A Bayesian analysis of retention functions (Q1775814) (← links)
• Accuracy, scope, and flexibility of models (Q1977902) (← links)
• The importance of complexity in model selection (Q1977911) (← links)
• Key concepts in model selection: Performance and generalizability (Q1977913) (← links)
• The minimum description length principle for pattern mining: a survey (Q2097441) (← links)
• An unsupervised neuromorphic clustering algorithm (Q2317470) (← links)
• Sources of complexity in subset choice (Q2483826) (← 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)
• Model selection by minimum description length: lower-bound sample sizes for the Fisher information approximation (Q2513825) (← links)
• A context-free language for binary multinomial processing tree models (Q2654150) (← links)
• Minimum description length method for facet matching (Q2751992) (← links)
• Model selection: beyond the Bayesian/frequentist divide (Q2896019) (← links)
• Nonstationary regression models with a lagged dependent variable (Q4337224) (← links)
• Model Selection and the Principle of Minimum Description Length (Q4419458) (← links)
• Counting probability distributions: Differential geometry and model selection (Q4528251) (← links)
• A Note on the Applied Use of MDL Approximations (Q4823699) (← links)
• An Introduction to Coding Theory and the Two-Part Minimum Description Length Principle (Q4831995) (← links)
• Formal Methods in FCA and Big Data (Q5054986) (← links)
• Nonparametric Regression as an Example of Model Choice (Q5451138) (← links)
• Few Paths, Fewer Words: Model Selection With Automatic Structure Functions (Q5743090) (← links)
• Explanatory and creative alternatives to the MDL principle (Q5938216) (← links)