Information and entropy econometrics—A review and synthesis
A Golan - Foundations and trends® in econometrics, 2008 - nowpublishers.com
The overall objectives of this review and synthesis are to study the basics of information-
theoretic methods in econometrics, to examine the connecting theme among these methods …
theoretic methods in econometrics, to examine the connecting theme among these methods …
Springer series in statistics
The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …
[图书][B] Principles and theory for data mining and machine learning
The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …
A cheat sheet for Bayesian prediction
This paper reviews the growing field of Bayesian prediction. Bayesian point and interval
prediction are defined and situated in statistical prediction more generally. Then, four …
prediction are defined and situated in statistical prediction more generally. Then, four …
Default priors for Bayesian and frequentist inference
DAS Fraser, N Reid, E Marras… - Journal of the Royal …, 2010 - academic.oup.com
We investigate the choice of default priors for use with likelihood for Bayesian and
frequentist inference. Such a prior is a density or relative density that weights an observed …
frequentist inference. Such a prior is a density or relative density that weights an observed …
A remark on the maximum entropy principle in uncertainty theory
G Ma - Soft Computing, 2021 - Springer
Uncertainty theory is a branch of axiomatic mathematics concerned with human's belief
degree. The maximum entropy principle states that the probability distribution with maximal …
degree. The maximum entropy principle states that the probability distribution with maximal …
On the Entropy and the Maximum Entropy Principle of Uncertain Variables
Y Liu, G Ma - Entropy, 2023 - mdpi.com
A new variance formula is developed using the generalized inverse of an increasing
function. Based on the variance formula, a new entropy formula for any uncertain variable is …
function. Based on the variance formula, a new entropy formula for any uncertain variable is …
An entropy‐based methodology for valuation of demand uncertainty reduction
AJ Fleischhacker, PW Fok - Decision Sciences, 2015 - Wiley Online Library
We propose a distribution‐free entropy‐based methodology to calculate the expected value
of an uncertainty reduction effort and present our results within the context of reducing …
of an uncertainty reduction effort and present our results within the context of reducing …
A frequentist framework of inductive reasoning
DR Bickel - Sankhya A, 2012 - Springer
A betting game establishes a sense in which confidence measures, confidence distributions
in the form of probability measures, are the only reliable inferential probability distributions …
in the form of probability measures, are the only reliable inferential probability distributions …
Model complexity in statistical manifolds: The role of curvature
Model complexity plays an essential role in its selection, namely, by choosing a model that
fits the data and is also succinct. Two-part codes and the minimum description length have …
fits the data and is also succinct. Two-part codes and the minimum description length have …