A
Amitava Mukherjee
Researcher at XLRI- Xavier School of Management
Publications - 96
Citations - 1609
Amitava Mukherjee is an academic researcher from XLRI- Xavier School of Management. The author has contributed to research in topics: Nonparametric statistics & Control chart. The author has an hindex of 20, co-authored 81 publications receiving 1218 citations. Previous affiliations of Amitava Mukherjee include Indian Institute of Technology Madras & Umeå University.
Papers
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Proceedings ArticleDOI
One Hotelling T 2 chart based on transformed data for simultaneous monitoring the frequency and magnitude of an event
Y. Cheng,Amitava Mukherjee +1 more
TL;DR: A typical bivariate gamma distribution with certain dependence structure is introduced based on which a kind of Hotelling T2 chart based on the transformed data is constructed for jointly monitoring of the shifts in the frequency and the magnitude of an event.
Journal ArticleDOI
Performance comparisons of distribution-free Shewhart-type Lepage and Cucconi schemes in monitoring complex process distributions:
TL;DR: The current study shows that in the presence of an additional parameter, especially when the shift in the shape parameter is substantial, the SL scheme is better; for a small change in shape, the SC scheme is more competitive.
Journal ArticleDOI
A Near-Nonparametric Partially Sequential Test for Monitoring Phase II Location Under Pairwise Dependence Between Two Phases
TL;DR: In this paper, a partially sequential test for monitoring the location parameter of a population at phase II when a standard sample of prefixed size from phase I population is available is introduced.
Journal ArticleDOI
A class of new nonparametric circular-grid charts for signal classification
TL;DR: Overall, one of the proposed CG Cucconi schemes is most effective in identifying a class of signals, whether it is a location shift or scale shift or a shift in both parameters, and it indicates the direction of the shifts in either or both the parameters.
Journal ArticleDOI
Distribution-free Phase-I scheme for location, scale and skewness shifts with an application in monitoring customers' waiting time
TL;DR: In this article, phase-I analysis of historical data from a statistical process is a strategic problem in Statistical Process Monitoring and Control, before the establishment of process stability, it is challenging.