Add to ORKGWe describe and experimentally investigate a method to construct forecasting algorithms for stationary and ergodic processes based on universal measures (or so-called universal data compressors). Using some geophysical and economical time series as examples, we show that the precision of thus obtained predictions is higher than that of known methods
In this thesis we develop several statistical methods to estimate high conditional quantiles to use ...
this paper we show that some simple prediction algorithms are optimal for this task in a sense that ...
This paper discusses the design and implementation of data compression applied to output from numeri...
AbstractWe consider forecasting systems which, when given an initial segment of a binary string, gue...
Time series forecasting plays an important role in financial activities since it allows investors to...
We show that data compression methods (or universal codes) can be applied for hypotheses testing in ...
Abstract. This paper applies three universal approximators for forecasting. They are the Artificial ...
We investigate the use of prediction as a means of reducing the model cost in lossless data compress...
This book shows the potential of entropy and information theory in forecasting, including both theor...
The transmission and storage of weather radar products will be an important problem for future weath...
We study universal prediction w.r.t. an indexed class of sources (e.g., parametric families) and gen...
Abstract The simplest way to forecast geophysical processes, an engineering problem with a widely re...
Although prediction schemes which are named "universal" are now abundant, very little has ...
summary:Important characteristics of any algorithm are its complexity and speed in real calculations...
In this thesis, we study sequential prediction problems. The goal is to devise and apply automatic s...
In this thesis we develop several statistical methods to estimate high conditional quantiles to use ...
this paper we show that some simple prediction algorithms are optimal for this task in a sense that ...
This paper discusses the design and implementation of data compression applied to output from numeri...
AbstractWe consider forecasting systems which, when given an initial segment of a binary string, gue...
Time series forecasting plays an important role in financial activities since it allows investors to...
We show that data compression methods (or universal codes) can be applied for hypotheses testing in ...
Abstract. This paper applies three universal approximators for forecasting. They are the Artificial ...
We investigate the use of prediction as a means of reducing the model cost in lossless data compress...
This book shows the potential of entropy and information theory in forecasting, including both theor...
The transmission and storage of weather radar products will be an important problem for future weath...
We study universal prediction w.r.t. an indexed class of sources (e.g., parametric families) and gen...
Abstract The simplest way to forecast geophysical processes, an engineering problem with a widely re...
Although prediction schemes which are named "universal" are now abundant, very little has ...
summary:Important characteristics of any algorithm are its complexity and speed in real calculations...
In this thesis, we study sequential prediction problems. The goal is to devise and apply automatic s...
In this thesis we develop several statistical methods to estimate high conditional quantiles to use ...
this paper we show that some simple prediction algorithms are optimal for this task in a sense that ...
This paper discusses the design and implementation of data compression applied to output from numeri...