The Effect of Estimation Error on Risk-Adjusted Survival Time CUSUM Chart Performance

2015 ◽  
Vol 32 (4) ◽  
pp. 1445-1452 ◽  
Author(s):  
Min Zhang ◽  
Yahui Xu ◽  
Zhen He ◽  
Xuejun Hou
Keyword(s):  
Survival Time ◽  
Estimation Error ◽  
Cusum Chart

scholarly journals Cumulative Sum Chart Modeled under the Presence of Outliers

Mathematics ◽  
2020 ◽  
Vol 8 (2) ◽  
pp. 269 ◽  
Author(s):  
Nasir Abbas ◽  
Mu’azu Ramat Abujiya ◽  
Muhammad Riaz ◽  
Tahir Mahmood
Keyword(s):  
Phase I ◽  
Phase Ii ◽  
Estimation Error ◽  
Signal Strength ◽  
Received Signal Strength ◽  
Cusum Chart ◽  
Cumulative Sum ◽  
Run Length ◽  
Design Structure ◽  
Control Limits

Cumulative sum control charts that are based on the estimated control limits are extensively used in practice. Such control limits are often characterized by a Phase I estimation error. The presence of these errors can cause a change in the location and/or width of control limits resulting in a deprived performance of the control chart. In this study, we introduce a non-parametric Tukey’s outlier detection model in the design structure of a two-sided cumulative sum (CUSUM) chart with estimated parameters for process monitoring. Using Monte Carlo simulations, we studied the estimation effect on the performance of the CUSUM chart in terms of the average run length and the standard deviation of the run length. We found the new design structure is more stable in the presence of outliers and requires fewer amounts of Phase I observations to stabilize the run-length performance. Finally, a numerical example and practical application of the proposed scheme are demonstrated using a dataset from healthcare surveillance where received signal strength of individuals’ movement is the variable of interest. The implementation of classical CUSUM shows that a shift detection in Phase II that received signal strength data is indeed masked/delayed if there are outliers in Phase I data. On the contrary, the proposed chart omits the Phase I outliers and gives a timely signal in Phase II.

The Poisson INAR(1) CUSUM chart under overdispersion and estimation error

2011 ◽  
Vol 43 (11) ◽  
pp. 805-818 ◽  
Author(s):  
Christian H. Weiß ◽  
Murat Caner Testik
Keyword(s):  
Estimation Error ◽  
Cusum Chart

Temporal Prediction Errors Affect Short-Term Memory Scanning Response Time

2016 ◽  
Vol 63 (6) ◽  
pp. 333-342
Author(s):  
Roberto Limongi ◽  
Angélica M. Silva
Keyword(s):  
Response Time ◽  
Short Term Memory ◽  
Estimation Error ◽  
Predictive Coding ◽  
Time Estimation ◽  
Prediction Errors ◽  
Memory Scanning ◽  
Short Term ◽  
Term Memory ◽  
Temporal Prediction

Abstract. The Sternberg short-term memory scanning task has been used to unveil cognitive operations involved in time perception. Participants produce time intervals during the task, and the researcher explores how task performance affects interval production – where time estimation error is the dependent variable of interest. The perspective of predictive behavior regards time estimation error as a temporal prediction error (PE), an independent variable that controls cognition, behavior, and learning. Based on this perspective, we investigated whether temporal PEs affect short-term memory scanning. Participants performed temporal predictions while they maintained information in memory. Model inference revealed that PEs affected memory scanning response time independently of the memory-set size effect. We discuss the results within the context of formal and mechanistic models of short-term memory scanning and predictive coding, a Bayes-based theory of brain function. We state the hypothesis that our finding could be associated with weak frontostriatal connections and weak striatal activity.

Influence of Channel Estimation Error on MIMO Multiplexing Using Precoding in Downlink OFDM Radio Access

2009 ◽  
Vol E92-B (5) ◽  
pp. 1553-1562
Author(s):  
Takashi ISOGAI ◽  
Mamoru SAWAHASHI ◽  
Hidekazu TAOKA ◽  
Kenichi HIGUCHI
Keyword(s):  
Channel Estimation ◽  
Estimation Error ◽  
Channel Estimation Error ◽  
Radio Access

Application Of Cusum Chart In Control Of Paper Quality

GIS Business ◽  
2020 ◽  
Vol 14 (6) ◽  
pp. 1062-1069
Author(s):  
S.Ramesh ◽  
B.A.Vasu
Keyword(s):  
Process Parameters ◽  
Manufacturing Process ◽  
Paper Industry ◽  
Primary Data ◽  
Cusum Chart ◽  
Paper Machine ◽  
Statistical Control ◽  
Operating Characteristics ◽  
Small Shift

This paper is an attempt to assess if the manufacturing process of paper machine is in statistical control thereby improving the quality of paper being produced in a paper industry at the time of process itself. Quality is the foremost criteria for achieving the business target. Therefore, emphasis was made on controlling the quality of paper at the time of manufacturing process itself, rather than checking the finished lots at a later time.  This control on quality will help the industry deduct the small shift in the process parameters and modify the operating characteristics at the time of production itself rather than receiving complaints from customers at a later stage.  This paper describes controlling quality at the time of manufacture itself and helps the industry to concentrate on quality at low cost. The researcher has collected primary data at a leading paper industry during October, 2019.  Though X-bar and Range charges were primarily used, CUSUM charts were used to sense the minor shifts in manufacturing process, to explore the possibility of adjusting process parameters during manufacture of paper.

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