Web Service for toxicant trigger valuation

Transcription

1 Individual Project Courses in the Research School of Computer Science Web Service for toxicant trigger valuation SUPERVISOR: DR. WARREN JIN PRESENTER : SHICHAO DONG(U )

2 Overview Experiment On Models Web Service Modification

3 Overview BurrliOZ NEC Web Service Extension Motivation

4 Outline BurrliOZ NEC Model Experiment Web Service Model Experiment Web Service Discussion Future Work Conclusion

5 BurrliOZ Model A statistical software package to help environmental managers to figure out trigger values of toxicant Burr Type III Log-Logistic

6 BurrliOZ Model A statistical software package to help environmental managers to figure out trigger values of toxicant Original : F x; θ = 1 1 (1+x c ) k, x > 0, c > 0, k > 0 Burr Type III Re-rewrite : F x; θ = [1 + ( b x a )c ] k, c > 0, k > 0

7 BurrliOZ Model A statistical software package to help environmental managers to figure out trigger values of toxicant Distribution Function : Log-Logistic F LL x = ( eμ x )1/θ

8 BurrliOZ Test A statistical software package to help environmental managers to figure out trigger values of toxicant

9 BurrliOZ Test A statistical software package to help environmental managers to figure out trigger values of toxicant Features:

10 BurrliOZ Web Service A statistical software package to help environmental managers to figure out trigger values of toxicant Shiny fromburrlioz2 R Language

11 BurrliOZ Web Service A statistical software package to help environmental managers to figure out trigger values of toxicant Shiny

12 BurrliOZ Web Service A statistical software package to help environmental managers to figure out trigger values of toxicant fromburrlioz2

13 BurrliOZ Web Service A statistical software package to help environmental managers to figure out trigger values of toxicant

14 BurrliOZ Web Service A statistical software package to help environmental managers to figure out trigger values of toxicant Data Summary

15 BurrliOZ Web Service A statistical software package to help environmental managers to figure out trigger values of toxicant Setting

16 BurrliOZ Web Service A statistical software package to help environmental managers to figure out trigger values of toxicant Download Report Report

17 BurrliOZ Web Service A statistical software package to help environmental managers to figure out trigger values of toxicant Plot

18 BurrliOZ Web Service A statistical software package to help environmental managers to figure out trigger values of toxicant Setting

19 Model NEC No effect concentration A Bayesian model for the NEC : E Y i ; x i = μ = α exp[ β x i γ I(x i γ)] NEC Model With I z = 1, z 0 0, z 0

20 NEC No effect concentration Model A Bayesian model for the NEC : E Y i ; x i = μ = α exp[ β x i γ I(x i γ)] With I z = 1, z 0 0, z 0 α is the response at zero/low dose concentrations β controls the rate of decay in the response γ is the NEC(no effect concentration)

21 NEC No effect concentration Test WinBUGS OpenBUGS BUGS = Bayesian inference Using Gibbs Sampling

22 NEC No effect concentration Test

23 NEC No effect concentration Test WinBUGS OpenBUGS WinBUGS OpenBUGS Result Repeatable No Yes Code Running No Yes Running on Linux No Yes Still update No Yes Same function Yes yes

24 NEC No effect concentration Library OpenBUGS Web Service User Shiny R code Interface Server Core

25 NEC No effect concentration Web Service

26 NEC No effect concentration Web Service

27 NEC No effect concentration Web Service

28 Discussion Cannot repeat the result Comparison Extension

29 Discussion Possible reason: has not updated for years Our solution: Using OpenBUGS

30 Discussion Paramet ers Mean Standard deviatio n P2.5 P50 P97.5 Alpha Beta Gamma Possible Reasons: Typo Error, Software problem Solution : continue using OpenBUGS

31 Discussion Comparison BurrliOZ BurrliOZ(WEB) NEC NEC(WEB) Interface Yes Yes No Yes OS Windows Any Any Any Platform Computer Computer, mobile device Computer Computer, mobile device Software.net library Web Browser WinBUGS Web Browser Programming No No Yes NO More flexible and accessible usage

32 Discussion Extension Features Features BurrliOZ BurrliOZ(WEB) NEC NEC(WEB) Loading data Models Priors distribution NA NA 1 2 Output result More features and more comparison

33 Future Work update the BurrliOZ package; improve the performance of BurrliOZ; more possible priors distributions in NEC. rewriting the front-end by using JavaScript; testing new possible models; comparing NOEC. vs NEC or other models using different tools and packages; using the same way in different fields

34 Conclusion Revisiting and experimenting Shao s and Fox s work, and we find there seems to be different from Fox s result with ours, we try to explain the difference and give our own solutions; implementing BurrliOZ into web service; implementing NEC into web service; providing figures with published quality extending Fox s work via providing more flexibility in the web service like normal distribution and Weibull distribution Experiment Web Service Extension

35 Reference [1] Tom Aldenberg and Wouter Slob. Confidence limits for hazardous concentrations based on logistically distributed noec toxicity data. Ecotoxicology and Environmental Safety, 25(1):48 63, [2] Christophe Andrieu, Nando De Freitas, Arnaud Doucet, and Michael I Jordan. An introduction to mcmc for machine learning. Machine learning, 50(1-2):5 43, [3] Kenneth E Biesinger, Leroy E Anderson, and John G Eaton. Chronic effects of inorganic and organic mercury ondaphnia magna: Toxicity, accumulation, and loss. Archives of environmental contamination and toxicology, 11(6): ,1982. [4] MRC Biostatistics. Background to bugs. [5] Irving W Burr. Cumulative frequency functions. The Annals of Mathematical Statistics, 13(2): , [6] CSIRO. Burrlioz 2.0 updates. [7] CSIRO. Burrlioz statistical software: a flexible approach to species protection. [8] A.J. Culyer. The Dictionary of Health Economics. Elgar Original Reference Series. Edward Elgar Publishing, Incorporated, [9] David R Fox. A bayesian approach for determining the no effect concentration and hazardous concentration in ecotoxicology. Ecotoxicology and Environmental Safety, 73(2): , [10] Jeffrey H Gove, Mark J Ducey, William B Leak, and Lianjun Zhang. Rotated sigmoid structures in managed uneven-aged northern hardwood stands: a look at the burr type iii distribution. Forestry, 81(2): , [11] SR Lindsay, GR Wood, and RC Woollons. Modelling the diameter distribution of forest stands using the burr distribution. Journal of Applied Statistics, 23(6): , [12] Ana M Pires, João A Branco, Ana Picado, and Elsa Mendonça. Models for the estimation of a no effect concentration. Environmetrics, 13(1):15 27, [13] r project. Introduction to r. [14] B.K. Shah and P.H. Dave. A note on log-logistic distribution. Journal of the MS University of Baroda (Science Number), 12:15 20, [15] Quanxi Shao. Estimation for hazardous concentrations based on noec toxicity data: an alternative approach. Environmetrics, 11(5): , [16] Pandu R Tadikamalla. A look at the burr and related distributions. International Statistical Review/Revue Internationale de Statistique, pages , [17] Pandu R Tadikamalla and Norman L Johnson. Systems of frequency curves generated by transformations of logistic variables. Biometrika, 69(2): , [18] Neal Thomas. Changes between winbugs and openbugs. openbugs.info/w.cgi/openvswin. [19] Neal Thomas. How it works. [20] Waloddi Weibull et al. A statistical distribution function of wide applicability. Journal of applied mechanics, 18(3): , 1951.

36 Thank you!

37 Q & A