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2013 Industrial Math/Stat Modeling Workshop for Graduate Students

2013 Industrial Math/Stat Modeling Workshop for Graduate Students . 발표자 : 장기훈. PREPERATION. 자기소개서 준비 합격통보 비자 발급 비행기 예약 회화연습 출국. 노스캐롤라이나. 한국. 11 시간 +6 시간 !!!!. SAMSI. Statistical and Applied Mathematical Sciences Institute NSF, Duke, NCSU, UNC, NISS

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2013 Industrial Math/Stat Modeling Workshop for Graduate Students

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  1. 2013 Industrial Math/Stat Modeling Workshop for Graduate Students 발표자 : 장기훈

  2. PREPERATION 자기소개서 준비 합격통보 비자 발급 비행기 예약 회화연습 출국

  3. 노스캐롤라이나 한국 11시간+6시간!!!!

  4. SAMSI Statistical and Applied Mathematical Sciences Institute NSF, Duke, NCSU, UNC, NISS SAMSI's  mission is to forge a synthesis of the statistical and the applied mathematical sciences to confront the very hardest and most important data, model-driven scientific challenges

  5. SAMSI 2013 Industrial Math/Stat Modeling Workshop for Graduate Students July 15-23, 2013 Objective was to expose graduate students in mathematics, engineering, and statistics to challenging and exciting real-world problems arising in industrial and government laboratory research

  6. SCHEDULE 8-9 am : Breakfast 9 am ~ 5 am : Working sessions Make the report Presentation of results

  7. PROJECTS Numerical Modeling and Simulation of Fluid Flow with Application to Current Environmental Challenges Burden of Sexual Transmitted Diseases in the US: Trend Analysis of Incidence Rates Photoresponsive Polymer Beam Design for Solar Concentrator Self-steering Heliostats Microbes and Molecules: A Microscopic Analysis of Asthma Network Analytics and Visualization in Healthcare Urban Route Planning from Aerial Imagery

  8. Burden of Chlamydia in the US: Trend Analysis of Incidence Rates RidouanBani, Anna D. Broido, Andrew F. Brouwer, Shih-Han Chang,Kihoon Jang, Qianqian Ma, Jiani Yin Faculty Mentors: Howard Chang, Emory Problem Presenter: Simone Gray, CDC

  9. Outline Chlamydia and reporting delays Graphical trends Modeling National and State level incidence rates Modeling incidence rates by population demographics Hierarchical modeling

  10. Chlamydia Most commonly reported bacterial STI in the US. Caused by bacterium Chlamydia trachomatis. Though it is often asymptomatic, especially in men, Chlamydia can lead to other serious illnesses in both men and women. Reporting delays (administrative) mean current incidence data is unavailable.

  11. National Incidence Rates: By Race African Americans had about 9 times higher incidence than Whites and Asians

  12. Objectives • Use available data 2000-2011 to project chlamydia incidence rates with quantified uncertainty for 2012-2013for: • The United States • Each state • Each demographic group • Sex • Race (American Indian, Asian, Black, Hispanic, White) • Create a hierarchical model to incorporate spatial effects on variations in incidence rates

  13. Poisson Regression • Assume incident cases follow a Poisson distribution • Natural for positive counts • Log-transformed rates are not normally distributed • Y= incident cases, λ = rate, N = population, xi = year, spatial, and demographic variables

  14. Model Assessment • Akaike information criterion (AIC) Average absolute relative deviation (AARD)

  15. National and State Model AARD calculated over 2000-2011 incident cases Population projected linearly Model 1: National level projections

  16. Demographic Model Note the importance of the Sex-Race interaction over the Year-Race interaction. AARD calculated over 2000-2011 incident cases

  17. Conclusions Incidence follows strong temporal trends that vary spatially and demographically. Poisson regression allows reasonable projection for recent and current incidence. Increased complexity does not necessarily improve predictions for aggregate data. Current approach for uncertainty quantification gives conservative estimates.

  18. Future Work Improve confidence in projections by training data on 2000-2009 data and testing on 2010-2011 for all models Include specific race-state interactions (particularly for American Indian populations in certain states) Include spatial correlation terms that decrease with distance. Investigate ways to relax the Poisson assumption and account for over-dispersion Project incidence beyond 2013

  19. PROGRAM

  20. WORKING Compile the data Analysis the data by using R Make simple statistic data Double check the data

  21. 소감 Good thing 여러 나라 학생과 학문적 교류 더 넓은 시각으로 수학을 공부 Bad thing 짧은 기간

  22. THANK YOU

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