TonyC

Nuclear Energy Trader

Total Posts: 1298 
Joined: May 2004 


thought my ACM digital library membership would get me these, [qs they all show up on the acm's digital library's ''portal'' pages], but somehow theyre not on the digital library and i cant seem to find a nonjstore instance via google
so if any kind NP'ers could send along copies of these i'd ge greatful
______________________________________________________ Changepoint detection of mean vector or covariance matrix shifts using multivariate individual observations Journal IIE Transactions Publisher Springer Netherlands ISSN 0740817X (Print) 15739724 (Online) Subject Biomedical and Life Sciences Issue Volume 32, Number 6 / June, 2000 DOI 10.1023/A:1007676020397 Pages 537549 SpringerLink Date Monday, November 01, 2004
Abstract A preliminary control chart is given for detecting a shift in the mean vector, the covariance matrix, or both, when multivariate individual observations are available. The data are partitioned after each observation in turn, and the likelihood ratio statistic for a shift is calculated. The control chart is obtained by plotting these statistics after dividing by the expected value under the condition of no shift. This adjustment is done in order to reduce the variation in sensitivity with the location of any shift. Using generalized inverses allows the detection of a shift after as few as two of the observations, or with as few as two remaining observations, or at any intermediate point. Multiple shifts often can be detected by recursive application of the method. When a shift is detected, the plotted statistic is divided into a part due to the shift in the sample mean vector and another part attributable to a shift in the sample covariance matrix. This is done for diagnostic purposes. Using simulation, approximate values are given for the expected values of the plotted statistics and an upper control limit.
__________________________________________________
Statistics: A Journal of Theoretical and Applied Statistics Publisher: Taylor & Francis Issue: Volume 39, Number 3 / June 2005 Pages: 221  246 URL: Linking Options DOI: 10.1080/02331880500062170
Surveillance of the covariance matrix of multivariate nonlinear time series
Przemysław śliwa A1 and Wolfgang Schmid A1
A1 Department of Statistics, Europe University, P.O. Box 1786, 15207, Frankfurt (Oder), Germany
Abstract:
In this paper, sequential procedures for the surveillance of the covariance matrices of multivariate nonlinear time series are introduced. Two different types of control charts are proposed. The first type is based on the exponential smoothing of each component of a local measure for the covariances. The control statistic is equal to the Mahalanobis distance of this quantity with its incontrol mean. In our second approach, the Mahalanobis distance is first determined and after that it is exponentially smoothed. We discuss three examples of local measures.
Several properties of the proposed schemes are discussed assuming the target process to be generated by a multivariate GARCH(1, 1) model. The generalization to the family of spherical distributions allows the modelling of frequently observed fat tails in financial data. Some results of an extensive Monte Carlo simulation study are provided in order to judge the performance of the presented control schemes. As a performance measure we use the average run length. An empirical example illustrates the importance of the fast detection of the changes in the covariance structure of the returns of financial assets.
___________________________________________________
A Note on Multivariate CUSUM Procedures John D. Healy Technometrics, Vol. 29, No. 4 (Nov., 1987), pp. 409412 doi:10.2307/1269451
Abstract
Cumulative sum (CUSUM) procedures are among the most powerful tools for detecting a shift from a good quality distribution to a bad quality distribution. This article discusses the natural application of CUSUM procedures to the multivariate normal distribution. It discusses two cases, detecting a shift in the mean vector and detecting a shift in the covariance matrix. As an example, the procedure is applied to measurements taken on optical fibers. 
flaneur/boulevardier/remittance man/energy trader 


braincat


Total Posts: 343 
Joined: Oct 2004 

 
FDAXHunter

Founding Member

Total Posts: 8372 
Joined: Mar 2004 


Same here. Only the "CUSUM Procedures" one. 
The Figs Protocol. 


doreilly


Total Posts: 100 
Joined: Feb 2006 

 
zMan


Total Posts: 42 
Joined: Nov 2006 


You guys are awesome!! 
per aspera ad astra 


nikol


Total Posts: 751 
Joined: Jun 2005 


Curious about CUSUM, thank you.



Mickey

Banned

Total Posts: 1 
Joined: Sep 2018 


The post is giving you nice views to learn. use 1$ domain hosting service. 



nikol


Total Posts: 751 
Joined: Jun 2005 


I have provided this in another thread, but for the sake of keeping all together here is duplicate.
Cusum Techniques for Technical Trading in Financial Markets
These seem also interesting  https://www.jstor.org/stable/1268068?seq=1#page_scan_tab_contents
"Note on a DistributionFree CUSUM Technique"
C. A. McGilchrist and K. D. Woodyer Technometrics Vol. 17, No. 3 (Aug., 1975), pp. 321325
 https://www.jstor.org/stable/1268068?seq=1#page_scan_tab_contents
"A NonParametric Approach to the ChangePoint Problem"
A. N. Pettitt Journal of the Royal Statistical Society. Series C (Applied Statistics) Vol. 28, No. 2 (1979), pp. 126135 

