Cost comparisons of modifiedX̅chart for autocorrelated observations

Cost comparisons of modified X chart for autocorrelated observations

This paper presents the economic design of modified X chart for autocorrelated data and comparison with the economic design of Shewhart’s X chart. An attempt has been made to counter autocorrelation by designing the modified X chart; as the cost of operating a process control system is an important element in the economic design of control charts. The economic designs of both modified and Shewh...

Confidence Intervals for Trend Estimates With Autocorrelated Observations

A two-sided Bernoulli-based CUSUM control chart with autocorrelated observations

Usually, in monitoring a proportion p < /em>, the binary observations are considered independent; however, in many real cases, there is a continuous stream of autocorrelated binary observations in which a two-state Markov chain model is applied with first-order dependence. On the other hand, the Bernoulli CUSUM control chart which is not robust to autocorrelation can be applied two-sided co...

Cost-Effective HITs for Relative Similarity Comparisons

Similarity comparisons of the form “Is object a more similar to b than to c?” form a useful foundation in several computer vision and machine learning applications. Unfortunately, an embedding of n points is only uniquely specified by n triplets, making collecting every triplet an expensive task. In noticing this difficulty, other researchers investigated more intelligent triplet sampling techn...

Mann-Kendall for autocorrelated data

The Mann-Kendall test is a commonly-used nonparametric test for time trend. However, the standard P-values obtained from it are based on an assumption of independence between observations (since the theory is that of the Kendall correlation). However, observations in time series are often autocorrelated: knowing that one observation is larger than the mean may tell you that the next observation...