A Simple Class of Bayesian Nonparametric Autoregression Models
نویسندگان
چکیده
منابع مشابه
A Simple Class of Bayesian Nonparametric Autoregression Models.
We introduce a model for a time series of continuous outcomes, that can be expressed as fully nonparametric regression or density regression on lagged terms. The model is based on a dependent Dirichlet process prior on a family of random probability measures indexed by the lagged covariates. The approach is also extended to sequences of binary responses. We discuss implementation and applicatio...
متن کاملAutoregression Approximation of a Nonparametric Diiusion Model
We consider a model of small diiusion type where the function which governs the drift term varies in a nonparametric set. We investigate discrete versions of this continuous model with respect to statistical equivalence, in the sense of the asymptotic theory of experiments. It is shown that an Euler diierence scheme as a discrete version of the stochastic diierential equation is asymptotically ...
متن کاملBayesian Nonparametric Models
‘ We have been looking at models that posit latent structure in high dimensional data. We use the posterior to uncover that structure. ‘ The two main types are mixtures (and variants, like mixed-membership) and factor models (like PCA, factor analysis, and others). ‘ A nagging concern for these methods is model selection—how do I choose the number of mixture components? the number of factors? ‘...
متن کاملSpatial Nonparametric Bayesian Models
The prior distribution is an essential ingredient of any Bayesian analysis, and it plays a major role in determining the final results. As such, Bayesians attempt to use prior distributions that have certain properties. Perhaps the main property is a desire to accurately reflect prior information, i.e., information external to the experiment at hand. We would supplement this vague property with...
متن کاملNonparametric Bayesian Kernel Models
Kernel models for classification and regression have emerged as widely applied tools in statistics and machine learning. We discuss a Bayesian framework and theory for kernel methods, providing a new rationalization of kernel regression based on nonparametric Bayesian models. Functional analytic results ensure that such a nonparametric prior specification induces a class of functions that span ...
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: Bayesian Analysis
سال: 2013
ISSN: 1936-0975
DOI: 10.1214/13-ba803