Approximations and Inequalities for Moving Sums

Methodology and Computing in Applied Probability - Tập 14 - Trang 597-616 - 2011
Joseph Glaz1, Joseph Naus2, Xiao Wang1
1Department of Statistics, University of Connecticut, Storrs, USA
2Department of Statistics Rutgers, The State University of New Jersey, Piscataway, USA

Tóm tắt

In this article accurate approximations and inequalities are derived for the distribution, expected stopping time and variance of the stopping time associated with moving sums of independent and identically distributed continuous random variables. Numerical results for a scan statistic based on a sequence of moving sums are presented for a normal distribution model, for both known and unknown mean and variance. The new R algorithms for the multivariate normal and t distributions established by Genz et al. (2010) provide readily available numerical values of the bounds and approximations.

Tài liệu tham khảo

Bauer P, Hackl P (1978) The use of MOSUMS for quality control. Technometrics 20:431–436 Bauer P, Hackl P (1980) An extension of the MOSUM technique to quality control. Technometrics 22:1-7 Chan HP (2009) Maxima of moving sums in a Poisson random field. Adv Appl Probab 41:647–663 Chu C-SJ, Hornik K, Kaun C-M (1995) MOSUM tests for parameter constancy. Biometrika 82:603–617 Esary JD, Proschan F, Walkup DW (1967) Association of random variables. Ann Math Stat 38:1466–1474 Genz A, Bretz F (2009) Computation of multivariate normal and t probabilities. Lecture notes in statistics, vol 195. Springer, New York Genz A, Bretz F, Miwa T, Mi X, Leisch F, Scheipl F, Hothorn T (2010) Multivariate normal and t distributions. Algorithm Version 0.9-9, R language documentation Glaz J, Johnson B (1988) Boundary crossing for moving sums. J Appl Probab 25:81–88 Glaz J, Naus J (1991) Tight bounds and approximations for scan statistics probabilities for discrete data. Ann Appl Probab 1:306–318 Glaz J, Naus J, Wallenstein S (2001) Scan statistics. Springer, New York Haiman G (1999) First passage time for some stationary process. Stoch Process their Appl 80:231–248 Haiman G (2007) Estimating the distribution of one-dimensional discrete scan statistics viewed as extremes of 1-dependent stationary sequences. J Stat Plan Inference 137:821–828 Holst L, Janson S (1990) Poisson approximations using the Stein–Chen method and coupling: number of exceedances of Gaussian random variables. Ann Probab 18:713–723 Naus JI (1982) Approximations for distributions of scan statistics. J Am Stat Assoc 77:177–183 Lai TL (1974) Control charts based on weighted sums. Ann Stat 2:134–147 Waldmann KH (1986) Bounds to the distribution of the run length in general quality-control schemes. Staistische Hefte 27:37–56 Westlund A (1984) Sequential moving sums of squares of OLS residuals in parameter stability testing. Qual Quant 18:261–273 Xia Z, Guo P, Zhao W (2009) Monitoring structural changes in generalized linear models. Commun Stat Theory Methods 38:1927–1947