Semi-parametric Robust Event Detection for Massive Time-Domain Databases

[1]  Pavlos Protopapas,et al.  Event Discovery in Time Series , 2009, SDM.

[2]  M. G. Pittau,et al.  A weakly informative default prior distribution for logistic and other regression models , 2008, 0901.4011.

[3]  Padhraic Smyth,et al.  Learning to detect events with Markov-modulated poisson processes , 2007, TKDD.

[4]  P. Perron,et al.  Estimating restricted structural change models , 2006 .

[5]  Charles Alcock,et al.  Statistical Methods for Detecting Stellar Occultations by Kuiper Belt Objects: The Taiwanese–American Occultation Survey , 2002, astro-ph/0209509.

[6]  Y. Benjamini,et al.  THE CONTROL OF THE FALSE DISCOVERY RATE IN MULTIPLE TESTING UNDER DEPENDENCY , 2001 .

[7]  A. Drake,et al.  The MACHO Project: Microlensing Detection Efficiency , 2000, astro-ph/0003392.

[8]  Xiao-Li Meng,et al.  The EM Algorithm—an Old Folk‐song Sung to a Fast New Tune , 1997 .

[9]  B. Peterson,et al.  The MACHO Project Dark Matter Search , 1995, astro-ph/9510104.

[10]  P. Perron,et al.  Estimating and testing linear models with multiple structural changes , 1995 .

[11]  Y. Benjamini,et al.  Controlling the false discovery rate: a practical and powerful approach to multiple testing , 1995 .

[12]  D. Andrews.  Tests for Parameter Instability and Structural Change with Unknown Change Point , 1993 .

[13]  B. Peterson,et al.  The MACHO Project - a Search for the Dark Matter in the Milky-Way , 1993 .

[14]  Adrian F. M. Smith,et al.  Hierarchical Bayesian Analysis of Changepoint Problems , 1992 .

[15]  A. Raftery,et al.  Bayesian analysis of a Poisson process with a change-point , 1986 .

[16]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[17]  A. F. Smith.  A Bayesian approach to inference about a change-point in a sequence of random variables , 1975 .