Optimal predictive model selection

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Optimal predictive model selection

Often the goal of model selection is to choose a model for future prediction, and it is natural to measure the accuracy of a future prediction by squared error loss. Under the Bayesian approach, it is commonly perceived that the optimal predictive model is the model with highest posterior probability, but this is not necessarily the case. In this paper we show that, for selection among normal l...

متن کامل

Parsimonious Function Representation and Optimal Predictive Model Selection

This paper proposes an intuitively appealing approach to function approximation that yields both parsimonious functional representations and optimal predictive models. Along the lines of the median probability model, the concept of prevalence is introduced and defined in terms of the posterior model probabilities. The posterior distribution of model size is used as the main device to determine ...

متن کامل

Predictive Model Selection

We consider the problem of selecting one model from a large class of plausible models. A predictive Bayesian viewpoint is advocated to avoid the speci cation of prior probabilities for the candidate models and the detailed interpretation of the parameters in each model. Using criteria derived from a certain predictive density and a prior speci cation that emphasizes the observables, we implemen...

متن کامل

Predictive Discretization During Model Selection

We present an approach to discretizing multivariate continuous data while learning the structure of a graphical model. We derive a joint scoring function from the principle of predictive accuracy, which inherently ensures the optimal trade-off between goodness of fit and model complexity including the number of discretization levels. Using the socalled finest grid implied by the data, our scori...

متن کامل

Optimal Inference After Model Selection

To perform inference after model selection, we propose controlling the selective type I error; i.e., the error rate of a test given that it was performed. By doing so, we recover long-run frequency properties among selected hypotheses analogous to those that apply in the classical (non-adaptive) context. Our proposal is closely related to data splitting and has a similar intuitive justification...

متن کامل

ذخیره 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: The Annals of Statistics

سال: 2004

ISSN: 0090-5364

DOI: 10.1214/009053604000000238