机器学习中的贝叶斯推理（二）——贝叶斯预测 - 知乎
贝叶斯预测（Bayesian Prediction）在本文中是指采用贝叶斯方法预测目标真值，其目标是求总体分布 p\left ( y|x \right) 的后验分布 p\left ( y|x, D \right) 。 贝叶斯预测的一般过程： STEP 1：计算模型参数的后验分布，注意这里求的是 分布函数 而不是参数的最大后验估计值； p\left ( \theta|D \right)=\frac {p\left ( D|\theta \right)p\left ( \theta \right)} {\int_ {\theta}\left [ p\left ( D|\theta \right)p\left ( \theta \right) \right]}
Bayesian Forecasting encompasses statistical theory and methods in time series anal-ysis and time series forecasting, particularly approaches using dynamic and state space models, though the underlying concepts and theoretical foundation relate to …
Bayesian forecasting in economics and finance: A modern review
2024年4月1日 · In Section 2 we provide a short tutorial on Bayesian forecasting. This begins with an outline of the Bayesian forecasting method, followed by an overview of the computational techniques used to implement the method. In Section 3 we then take the reader on a potted chronological tour of Bayesian forecasting, up to the present day. We begin by ...
Bayesian Forecasting in Economics and Finance: A Modern Review
2022年12月7日 · The Bayesian statistical paradigm provides a principled and coherent approach to probabilistic forecasting. Uncertainty about all unknowns that characterize any forecasting problem -- model, parameters, latent states -- is able to be quantified explicitly, and factored into the forecast distribution via the process of integration or averaging.
In Section 2 we provide a short tutorial on Bayesian forecasting. This begins with an outline of the Bayesian forecasting method, followed by an overview of the computational techniques used to implement the method. In Section 3 we then take the reader on a potted chronological tour of Bayesian forecasting, up to the present day.
Bayesian time series and forecasting is a very broad field and any attempt at other than a very selective and personal overview of core and recent areas would be foolhardy. This chapter therefore selectively notes some key models and ideas, leavened with extracts from a few time series analysis and forecasting examples.
Chapter 1 Bayesian Forecasting - ScienceDirect
2006年1月1日 · Bayesian forecasting is a natural product of a Bayesian approach to inference. The Bayesian approach in general requires explicit formulation of a model, and conditioning on known quantities, in order to draw inferences about unknown ones.
Chapter 1 Bayesian Forecasting - ScienceDirect
2006年1月1日 · In Bayesian forecasting, one simply takes a subset of the unknown quantities to be future values of some variables of interest. This chapter presents the principles of Bayesian forecasting, and describes recent advances in computational capabilities for applying them that have dramatically expanded the scope of applicability of the Bayesian ...
Chapter 1 Bayesian Forecasting - Penn State
This chapter presents the principles of Bayesian forecasting, and describes recent advances in computational capabilities for applying them that have dramatically expanded the scope of applicability of the Bayesian approach. It describes historical developments and the analytic compromises that were necessary prior to recent developments, the ...
Bayesian Forecasting and Dynamic Models | SpringerLink
We describe the structure and theory of classes of dynamic models and their uses in forecasting and time series analysis. The principles, models and methods of Bayesian forecasting and time - ries analysis have been developed extensively during the last thirty years.