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Original Articles

Sufficient Reduction in Multivariate Surveillance

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Pages 1821-1838 | Received 15 Aug 2009, Accepted 18 Feb 2010, Published online: 18 Mar 2011

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Read on this site (5)

S. Siripanthana & E. C. Stillman. (2016) Sufficient reduction methods for multivariate time-dependent health surveillance data. Communications in Statistics - Theory and Methods 45:4, pages 950-966.
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Marianne Frisén. (2014) Spatial outbreak detection based on inference principles for multivariate surveillance. IIE Transactions 46:8, pages 759-769.
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Constantinos I. Siettos & Lucia Russo. (2013) Mathematical modeling of infectious disease dynamics. Virulence 4:4, pages 295-306.
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Vasyl Golosnoy & Jens Hogrefe. (2013) Signaling NBER turning points: a sequential approach. Journal of Applied Statistics 40:2, pages 438-448.
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Linus Schiöler & Marianne Frisén. (2012) Multivariate outbreak detection. Journal of Applied Statistics 39:2, pages 223-242.
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Articles from other publishers (4)

Sawaporn Hinsheranan & Eleanor C. Stillman. (2021) The robustness of sufficient reduction methods for detecting shifts of various types in multivariate processes. Quality and Reliability Engineering International 37:5, pages 2276-2287.
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Flavie Vial, Wei Wei & Leonhard Held. (2016) Methodological challenges to multivariate syndromic surveillance: a case study using Swiss animal health data. BMC Veterinary Research 12:1.
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Aline Piroutek, Renato Assunção & Thaís Paiva. (2014) Space-time prospective surveillance based on Knox local statistics. Statistics in Medicine 33:16, pages 2758-2773.
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Marianne Frisén. (2011) Methods and evaluations for surveillance in industry, business, finance, and public health. Quality and Reliability Engineering International 27:5, pages 611-621.
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