Average Life Prediction Based on Incomplete Data

Average Life Prediction Based on Incomplete Data

The two-parameter exponential distribution can often be used to describe the lifetime of products for example, electronic components, engines and so on. This paper considers a prediction problem arising in the life test of key parts in high speed trains. Employing the Bayes method, a joint prior is used to describe the variability of the parameters but the form of the prior is not specified and...

Statistical Prediction Based on Censored Life Data

This article describes methods for using censored life data to construct prediction bounds or intervals for future outcomes. Both new-sample prediction (e.g., using data from a previous sample to make predictions on the future failure time of a new unit) and within-sample prediction problems (e.g., predicting the number of future failures from a sample, based on early data from that sample) are...

Ensemble-based Top-k Recommender System Considering Incomplete Data

Recommender systems have been widely used in e-commerce applications. They are a subclass of information filtering system, used to either predict whether a user will prefer an item (prediction problem) or identify a set of k items that will be user-interest (Top-k recommendation problem). Demanding sufficient ratings to make robust predictions and suggesting qualified recommendations are two si...

Image Reconstruction from Incomplete Data

Image Reconstruction from Incomplete Data