In practice, the data  collected often systematically deviate from their actual values; a typical example is the underreporting of data in social sciences, ecology and epidemiology. Therefore, direct application of traditional statistical methods to the data may lead to incorrect inferences. In this paper, we propose a new test for serial dependence or cross-dependence of stationary or periodic time series and use a block bootstrap method to mimic the distribution of the test statistics. The test shows desirable performance in simulated data with underreporting and is used to detect factors of dengue transmission and cardiovascular disease.

6月16日
2:00pm - 3:00pm
地點
Room 2463 (Lifts 25/26)
講者/表演者
Prof. Yingcun XIA
Department of Statistics and Applied Probability, National University of Singapore
主辦單位
Department of Mathematics
聯絡方法
付款詳情
對象
Alumni, Faculty and staff, PG students, UG students
語言
英語
其他活動
3月24日
研討會, 演講, 講座
IAS / School of Science Joint Lecture - Pushing the Limit of Nonlinear Vibrational Spectroscopy for Molecular Surfaces/Interfaces Studies
Abstract Surfaces and interfaces are ubiquitous in Nature. Sum-frequency generation vibrational spectroscopy (SFG-VS) is a powerful surface/interface selective and sub-monolayer sensitive spect...
11月22日
研討會, 演講, 講座
IAS / School of Science Joint Lecture - Leveraging Protein Dynamics Memory with Machine Learning to Advance Drug Design: From Antibiotics to Targeted Protein Degradation
Abstract Protein dynamics are fundamental to protein function and encode complex biomolecular mechanisms. Although Markov state models have made it possible to capture long-timescale protein co...