Abstract. This paper presents k-NN as an approximator for time series prediction problems. The main advantage of this approximator is its simplicity. Despite the simplicity, k-NN c...
Predicting stock market movements is always difficult. Investors try to guess a stock's behavior, but it often backfires. Thumb rules and intuition seems to be the major indi...
When large amount of statistical information about power system component failure rate is available, statistical parametric models can be developed for predictive maintenance. Oft...
Miroslav Begovic, Petar M. Djuric, Joshua Perkel, ...
Abstract. Gene expression profiling strategies have attracted considerable interest from biologist due to the potential for high throughput analysis of hundreds of thousands of gen...
A family of probabilistic time series models is developed to analyze the time evolution of topics in large document collections. The approach is to use state space models on the n...