Outlier detection and hypothesis testing are two important processes in statistical analysis, each serving its own purpose but sometimes intersecting in practice. Outlier detection involves ...

Abstract: Outlier hypothesis testing is studied in a universal setting. Multiple sequences of observations are collected, a small subset of which are outliers. A sequence is considered an outlier if ...

Abstract: Process variability effects and subtle defect mechanisms in deeply scaled analog/mixed-signal/RF (AMS) silicon technologies combine in malicious ways to increase DPPMs of mixed-signal ...

Determining whether a data point is an "outlier" - a result that does not fit, is too high or too low, is extreme or discordant - is difficult when using small data sets, such as the data from three, ...

#Outlier Detection In this project we are analysing the property prices available in the city of banglore.For this we are using outlier detection and using house_price.csv.Here,we examined price per ...