Dynamic model averaging in large model spaces using dynamic Occam׳s window
نویسندگان
چکیده
منابع مشابه
Dynamic Model Averaging in Large Model Spaces Using Dynamic Occam's Window.
Bayesian model averaging has become a widely used approach to accounting for uncertainty about the structural form of the model generating the data. When data arrive sequentially and the generating model can change over time, Dynamic Model Averaging (DMA) extends model averaging to deal with this situation. Often in macroeconomics, however, many candidate explanatory variables are available and...
متن کاملForecasting Ination Using Dynamic Model Averaging
We forecast quarterly US ination based on the generalized Phillips curve using econometric methods which incorporate dynamic model averaging. These methods not only allow for coe¢ cients to change over time, but also allow for the entire forecasting model to change over time. We nd that dynamic model averaging leads to substantial forecasting improvements over simple benchmark regressions and...
متن کاملForecasting in Dynamic Factor Models Using Bayesian Model Averaging
This paper considers the problem of forecasting in dynamic factor models using Bayesian model averaging. Theoretical justi cations for averaging across models, as opposed to selecting a single model, are given. Practical methods for implementing Bayesian model averaging with factor models are described. These methods involve algorithms which simulate from the space de ned by all possible models...
متن کاملDynamic logistic regression and dynamic model averaging for binary classification.
We propose an online binary classification procedure for cases when there is uncertainty about the model to use and parameters within a model change over time. We account for model uncertainty through dynamic model averaging, a dynamic extension of Bayesian model averaging in which posterior model probabilities may also change with time. We apply a state-space model to the parameters of each mo...
متن کاملDynamic Graphs in the Sliding-Window Model
We present the first algorithms for processing graphs in the slidingwindow model. The sliding window model, introduced by Datar et al. (SICOMP 2002), has become a popular model for processing infinite data streams in small space when older data items (i.e., those that predate a sliding window containing the most recent data items) are considered “stale” and should implicitly be ignored. While p...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: European Economic Review
سال: 2016
ISSN: 0014-2921
DOI: 10.1016/j.euroecorev.2015.07.013