Zobrazeno 41 - 50
of 105
pro vyhledávání: '"Joseph Glaz"'
Autor:
Joseph Glaz
Publikováno v:
Computational Statistics & Data Analysis. 14:213-227
The scan statistic is used in many areas of science to test the null hypothesis of uniformity against a clustering alternative. In this article product-type approxiamations and Bonferroni-type upper bounds are derived for the tail probabilities of th
Publikováno v:
Naval Research Logistics. 39:97-114
Autor:
Jie Chen, Joseph Glaz
Publikováno v:
Scan Statistics ISBN: 9780817647483
In this chapter, approximations for distributions of a two- dimensional maximum scan score-type statistic and a minimum p-value scan statistic are derived for independent and identically distributed binomial and Poisson observations. Both uncondition
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f5816e94988b4f03ac0abd519b241c0e
https://doi.org/10.1007/978-0-8176-4749-0_5
https://doi.org/10.1007/978-0-8176-4749-0_5
Publikováno v:
Journal of Forecasting. 10:445-463
Simultaneous prediction intervals for forecasts from time series models that contain L (L ≤ 1) unknown future observations with a specified probability are derived. Our simultaneous intervals are based on two types of probability inequalities, i.e.
Autor:
Joseph Glaz, Nalini Ravishanker
Publikováno v:
Statistics & Probability Letters. 12:57-63
New simultaneous prediction intervals for multiple forecasts from ARIMA models based on the Bonferroni-type and the product-type inequalities are introduced. These prediction intervals are compared with the marginal prediction intervals used in forec
Publikováno v:
ICASSP
In this article we introduce a sequential procedure for detecting a target using distributed sensors in a two dimensional region. The detection is carried out in a mobile fusion center (in a way familiar to hockey fans, we envision this as a Zamboni
Autor:
Jie Chen, Joseph Glaz
Publikováno v:
Recent Advances in Applied Probability ISBN: 0387233784
In this article Poisson-type and compound Poisson approximations are discussed for a multiple scan statistic for Binomial and Poisson data in one and two dimensions. Numerical results are presented to evaluate the performance of these approximations.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8aef37d4b71331440397bf087256dc3d
https://doi.org/10.1007/0-387-23394-6_4
https://doi.org/10.1007/0-387-23394-6_4
Scan statistics is currently one of the most active and important areas of research in applied probability and statistics, having applications to a wide variety of fields: archaeology, astronomy, bioinformatics, biosurveillance, molecular biology, ge