Environmental and Ecological Statistics with R

Environmental and Ecological Statistics with R

Volumn , Issue , 2009, Pages 1-421

  Qian, Song S ^a  

^a DUKE UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85122717787     PISSN: None     EISSN: None     Source Type: Book    
DOI: None     Document Type: Book

References (111)

1. C.W. Anderson, T.M. Wood, and J.L. Morace. Distribution of dissolved pesticides and other water quality constituents in small streams, and their relation to land use, in the Willamette River Basin, Oregon. Technical report, U.S. Geological Survey, Water-Resources Investigations Report 97-4268, Portland Oregon, 1997.
2. D.R. Anderson, K.P. Burnham, and W.L. Thompson. Null hypothesis testing: Problems, prevalence, and an alternative. Journal of Wildlife Management, 64:912-923, 2000.
3. E. Anderson. The irises of the Gaspe Peninsula. Bulletin of the American Iris Society, 59:2-5, 1935.
4. M. Banerjee and I.W. McKeague. Confidence sets for split points in decision trees. The Annals of Statistics, 35(2):543-574, 2007.
5. D.M. Bates and D.G. Watts. Nonlinear Regression Analysis and Its Applications. Wiley Series in Probability and Statistics. Wiley, New York, 2007.
6. J.H. Bennett, editor. Collected Papers of R.A. Fisher. Adelaide: University of Adelaide, 1971.
7. P.M. Berthouex and L.C. Brown. Statistics for Environmental Engineers. Lewis Publishers, Boca Raton, 1994.
8. J.A. Bishop. An experimental study of the cline of industrial melanism in biston betularia (l.) (lepidoptera) between urban liverpool and rural north wales. The Journal of Animal Ecology, 41(1):209-243, 1972.
9. P. Bloomfield, A. Royle, and Q. Yang. Accounting for meteorological effects in measuring urban ozone levels and trends. Technical report, Technical Report # 1, National Institute of Statistical Sciences, Research Triangle Park, NC, 1993.
10. G.E.P. Box. Science and statistics. Journal of the American Statistical Association, 71(356):791-799, 1976.
11. G.E.P. Box and D.R. Cox. An analysis of transformations (with discussion). Journal of the Royal Statistical Society, B, 26:211-246, 1964.
12. L. Breiman. Random forests. Machine Learning, 45(1):5-32, 2001.
13. L. Breiman, J.H. Friedman, R. Olshen, and C.J. Stone. Classification and Regression Trees. Wadsworth International Group, Belmont, CA, 1984.
14. P. Biihlmann and B. Yu. Analyzing bagging. The Annals of Statistics, 30(4): 927-961, 2002.
15. R.K. Carey. Modeling N2O emissions from agricultural soils using a multilevel linear regression. Master's thesis, Nicholas School of the Environment, Duke University, Durham, NC, 2007.
16. J.M. Chambers and T.J. Hastie, editors. Statistical Models in S. CRC Press, Inc., Boca Raton, FL, USA, 1991. ISBN 0412052911.
17. C.J. Chen, Y.C. Chuang, T.M. Lin, and H.Y. Wu. Malignant neoplasms among residents of a blackfoot diseaseendemic area in taiwan: High-arsenic artesian well water and cancers. Cancer Research, 45:5895-5899, 1985.
18. L.A. Clark and D. Pregibon. Tree-based models. In J.M. Chambers and T.J. Hastie, editors, Statistical Models in S. Wadsworth & Brooks, Pacific Grove, CA, 1992.
19. R.B. Cleveland, W.S. Cleveland, J.E. Mcrae, and I. Terpenning. STL: A seasonal-trend decomposition procedure based on loess. Journal of Official Statistics, 6(1):3-73, 1990.
20. W.S. Cleveland. Visualizing Data. Hobart Press, Summit, NJ, 1993.
21. J. Cohen. Statistical Power Analysis for the Behavioral Sciences. Lawrence Erlbaum Associates, Hillsdale, NJ, 1988.
22. T.F. Cuffney and J.A. Falcone. Derivation of nationally consistent indices representing urban intensity within and across nine metropolitan areas of the conterminous united states. Technical report, U.S. Geological Survey, Scientific Investigations Report 2008-5095, 36 pp., 2008.
23. T.F. Cuffney, H. Zappia, E.M.P. Giddings, and J.F. Coles. Effects of urbanization on benthic macroinvertebrate assemblages in contrasting environmental settings: Boston, Massachusetts; Birmingham, Alabama; and Salt Lake City, Utah. American Fisheries Society Symposium, 47: 361-407, 2005.
24. C.C. Daehler and D.R. Strong. Can you bottle nature? The roles of microcosms in ecological research. Ecology, 77:663-664, 1996.
25. J.H. Davis. The natural features of southern Florida, especially the vegetation, and the everglades. Technical report, Florida Geological Survey Bulletin, No. 25, 1943.
26. S.M. Davis and J.C. Ogden, editors. Everglades: The Ecosystem and Its Restoration. St. Lucie Press, Delray Beach, FL, 1994.
27. G. De'ath and K.E. Fabricius. Classification and regression trees: A powerful yet simple technique for the analysis. Ecology, 81(11):3178-3192, 2000.
28. R. Eckhardt. Stan Ulam, John von Neumann, and the Monte Carlo method. Los Alamos Science, 15:131-143, 1987.
29. B. Efron and R.J. Tibshirani. An Introduction to the Bootstrap. Chapman and Hall, New York, 1993.
30. A.M. Ellison, E.J. Farnsworth, and R.R. Twilley. Facultative mutualism between red mangroves and root-fouling sponges in berlizean mangal. Ecology, 77(8):2431-2444, 1996.
31. G.R. Finch, C.W. Daniels, E.K. Black, F.W. Schaefer, and M. Belosevic. Dose response of Cryptosporidium parvum in outbred neonatal cd-1 mice. Applied and Environmental Microbiology, 59(11):3661-3665, 1993.
32. R.A. Fisher. On the mathemetical foundations of theoretical statistics. Philosophical Transactions of the Royal Society of London, Series A, 222: 309-368, 1922.
33. R.A. Fisher. The use of multiple measurements in taxonomic problems. Annals of Eugenics, 7, Part II: 179-188, 1936.
34. R.A. Fisher. Statistical methods and scientific induction. Journal of the Royal Statistical Society, B, 17:69-78, 1955.
35. R.A. Fisher. Statistical Methods for Research Workers. Oliver and Boyd, Edinburgh. (14th edition reprinted in 1970), 1st edition, 1925.
36. J. Fox. The R Commander: A basic-statistics graphical user interface to R. Journal of Statistical Software, 14(9), 2005.
37. A.S. Friedlaender, P.N. Halpin, S.S. Qian, G.L. Lawson, P.H. Wiebe, D. Thiele, and A.J. Read. Whale distribution in relation to prey abundance and oceanographic processes in shelf waters of the Western Antarctic Peninsula. Marine Ecology Progress Series, 317:297-310, 2006.
38. A. Gelman. Analysis of variance-Why it is more important than ever (with discussion). The Annals of Stastics, 33(1):1-53, 2005.
39. A. Gelman and J. Hill. Data Analysis Using Regression and Multilevel/Hierarchical Models. Cambridge University Press, New York, 2007.
40. A. Gelman, J.B. Carlin, H.S. Stern, and D.B. Rubin. Bayesian Data Analysis. Chapman & Hall, London, 2nd edition, 2003.
41. A. Gelman, J. Hill, and M. Yajima. Why we (usually) don't have to worry about multiple comparisons. Technical report, Department of Statistics, Columbia University, 2008. URL http://www.stat.columbia.edu/~gelman/research/unpublished/multiple2.pdf.
42. W.R. Gilks, D.J. Spiegelhalter, and S. Richardson. Practical Markov Chain Monte Carlo. Chapman and Hall, London. UK, 1995.
43. R.J. Gilliom and D.R. Helsel. Estimation of distribution parameters for censored trace level water quality data 1: Estimation techniques. Water- Resources Research, 22:135-146, 1986.
44. A. Gleit. Estimation of small normal data sets with detection limits. Environmental Science and Technology, 19:1201-1206, 1985.
45. N.J. Gotelli and A.M. Ellison. A Primer of Ecological Statistics. Sinauer Associates, Inc. Publishers, Sunderland, MA., 2004.
46. A. Guisan and N.E. Zimmermann. Predictive habitat distribution models in ecology. Ecological Modelling, 135(2-3):147-186, 2000.
47. W. Hardle. Smoothing Techniques: With Implementation in S. SpringerVerlag, New York, 1991.
48. T.J. Hastie and R.J. Tibshirani. Generalized Additive Models. Chapman and Hall, London, 1990.
49. J.P. Hayes and R.J. Steidl. Statistical power analysis and amphibian population trends. Consevation Biology, 11(1):273-275, 1997.
50. D.R. Helsel and R.J. Gilliom. Estimation of distribution parameters for censored trace level water quality data 2: Verification and applications. Water Resources Research, 22:147-155, 1986.
51. J.M. Hoenig and D.M. Heisey. The abuse of power: The pervasive fallacy of power calculations for data analysis. The American Statistician, 55(1):1-6, 2001.
52. D. Hume. An Inquiry Concerning Human Understanding. The Clarendon Press, Oxford, 1777.
53. J.P.A. Ioannidis. Why most published research findings are false. PLoS Medicine, 2(8):e124 doi:10.1371/journal.pmed.0020124, 2005.
54. J.L. Jacobson and S.W. Jacobson. A 4-year followup study of children born to consumers of Lake Michigan fish. Journal of Great Lakes Research, 19: 776-783, 1993.
55. J.L. Jacobson and S.W. Jacobson. Intellectual impairment in children exposed to polychlorinated biphenyls in utero. The New England Journal of Medicine, 335:783-789, 1996.
56. D.G. Korich, M.M. Marshall, H.V. Smith, J. O'Grady, C.R. Bukhari, Z. Fricker, J.P. Rosen, and J.L. Clancy. Inter-laboratory comparison of the cd-1 neonatal mouse logistic dose-response model for Cryptosporidium parvum oocysts. Journal of Eukaryotic Microbiology, 47(3):294-298, 2000.
57. P. Kuhnert and B. Venables. An Introduction to R: Software for Statistical Modelling & Computing. Technical report, CSIRO Mathematical and Information Sciences, Cleveland, Australia, 2005. URL http://cran. r-pro j ect. org/doc/contrib/Kuhnert+Venables-R_Course JJotes. zip.
58. J. Lenhard. Models and statistical inference: The controversy between Fisher and Neyman-Pearson. The British Journal for the Philosophy of Science, 57(1):69-91, 2006.
59. S.S. Light and J.W. Dineen. Water control in the everglades: A historical perspective. In S.M. Davis and J.C. Ogden, editors, Everglades: the Ecosystem and Its Restoration, pages 47-84. St. Lucie Press, Delray Beach, FL, 1994.
60. C.P. Madenjian, R.J. Hesselberg, T.J. Desorcie, L.J. Schmidt, Stedman. R.M., L.J. Begnoche, and D.R. Passino-Reader. Estimate of net trophic transfer efficiency of PCBs to Lake Michigan lake trout from their prey. Environmental Science and Technology, 32:886-891, 1998.
61. O. Malve and S.S. Qian. Estimating nutrients and chlorophyll a relationships in Finnish lakes. Environmental Science and Technology, 40(24):7848-7853, 2006.
62. P. McCullagh and J.A. Nelder. Generalized Linear Models. Chapman & Hall, London, 1989.
63. G. McMahon and T.F. Cuffney. Quantifying urban intensity in drainage basins for assessing stream ecological conditions. Journal of the American Water Resources Association, 36(6):1247-1261, 2000.
64. K.H. Morales, L. Ryan, T.L. Kuo, M.M. Wu, and C.J. Chen. Risk of internal cancers from arsenic in drinking water. Environmental Health Perspectives, 108:655-661, 2000.
65. V.M.R. Muggeo. Estimating regression models with unknown break-points. Statistics in Medicine, 22(19):3055-3071, 2003.
66. National Research Council. Arsenic in Drinking Water. National Academy Press, Washington, D.C., 1999.
67. W.R. Ott. Environmental Statistics and Data Analysis. Lewis Publishers, Boca Raton, 1995.
68. R.H. Peters. A Critique for Ecology. Cambridge University Press, 1991.
69. J.C. Pinheiro and D.M. Bates. Mixed-Effects Models in S and S-PLUS. Springer-Verlag, New York, 2000.
70. K.P. Popper. The Logic of Scientific Discovery. Hutchinson Education (reprinted 1992 by Routledge), London, 1959.
71. Qian. A nonparametric Bayesian model of phosphorus retention. PhD thesis, Nicholas School of the Environment, Duke University, 1995.
72. Qian and C.W. Anderson. Exploring factors controlling variability of pesticide concentrations in the Willamette River Basin using tree-based models. Environmental Science and Technology, 33:3332-3340, 1999.
73. Qian and M. Lavine. Setting standards for water quality in the Everglades. Chance, 16(3):10-16, 2003.
74. Qian and C.J. Richardson. Estimating the long-term phosphorus accretion rate in the Everglades: A Bayesian approach with risk assessment. Water Resources Research, 33(7):1681-1688, 1997.
75. Qian and Z. Shen. Ecological applications of multilevel analysis of variance. Ecology, 88(10):2489-2495, 2007.
76. Qian, M.E. Borsuk, and C.A. Stow. Seasonal and long-term nutrient trend decomposition along a spatial gradient in the Nuese River watershed. Environmental Science and Technology, 34:4474-4482, 2000.
77. Qian, R.S. King, and C.J. Richardson. Two statistical methods for the detection of environmental thresholds. Ecological Modelling, 166:87-97, 2003.
78. Qian, A. Schulman, J. Koplos, A. Kotros, and P. Kellar. A hierarchical modeling approach for estimating national distributions of chemicals in public drinking water systems. Environmental Science and Technology, 38 (4):1176-1182, 2004.
79. Qian, K. Linden, and M. Donnelly. A Bayesian analysis of mouse infectivity data to evaluate the effectiveness of using ultraviolet light as a drinking water disinfectant. Water Research, 39:4229-4239, 2005.
80. F.L. Ramsey and D.W. Schafer. The Statistical Sleuth, A Course in Methods of Data Analysis. Duxbury, Pacific Grove, CA., 2002.
81. K.H. Reckhow and S.S. Qian. Modeling phorsphorus trapping in wetland using generalized additive models. Water Resources Research, 30(11):3105-3114, 1994.
82. K.H. Reckhow, J.T. Clements, and R.C. Dodd. Statistical evaluation of mechanistic water quality models. Journal of Environmental Engineering, 116(2):250-268, 1990.
83. C.J. Richardson, editor. The Everglades Experiments: Lessons for Ecosystem Restoration. Springer-Verlag, New York, 2007.
84. C.J. Richardson and S.S. Qian. Long-term phosphorus assimilative capacity in freshwater wetlands: A new paradigm for sustaining ecosystem structure and function. Environmental Science and Technology, 33(10):1545-1551, 1999.
85. B.D. Ripley. Pattern Recognition and Neural Networks. Cambridge University Press, Cambridge, UK, 1996.
86. K.W. Rizzardi. Alligators and litigators: A recent history of Everglades regulation and litigation. Florida Bar Journal, March:18, 2001.
87. C.P. Robert and G. Casella. Monte Carlo Statistical Methods. Springer, 2004.
88. J.T. Rotenberry and J.A. Wiens. Statistical power analysis and communitywide patterns. The American Naturalist, 125(1):164-168, 1985.
89. C. Ruchdeschel, C.R. Shoop, and R.D. Kenney. On the sex ratio of juvenile Lepidochelys kempii in georgia. Chelonian Conservation and Biology, 4(4): 860-863, 2005.
90. L.M. Ryan. Epidemiologically based environmental risk assessment. Statistical Science, 18(4):466-480, 2003.
91. M.D. Schwartz and J.M. Caprio. North American First Leaf and First Bloom Lilac Phenology Data. Data contribution series # 2003-078., IGBP PAGES/World Data Center for Paleoclimatology, NOAA/NGDC Paleoclimatology Program, Boulder CO, USA., 2003. URL ftp://ftp. ncdc. noaa. gov/pub/data/paleo/phenology/north^america_lilac. txt.
92. M.D. Schwartz, R. Ahas, and A. Aasa. Onset of spring starting earlier across the Northern Hemisphere. Global Change Biology, 12(2):343-351, 2006.
93. D.G. Scroggin. Detection limits and variability in testing methods for environmental pollutants: Misuse may produce significant liabilities. Hazardous Waste and Hazardous Materials, 11(1): 1-4, 1994.
94. A.F. M. Smith. A Bayesian approach to inference about a change-point in a sequence of random variables. Biometrika, 62(2):407-416, 1975. doi: 10.1093/biomet/62.2.407.
95. E.P. Smith, K. Ye, C. Hughes, and L. Shabman. Statistical assessment of violations of water quality standards under section 303(d) of the clean water act. Environmental Science and Technology, 35(3):606-612, 2001.
96. R.A. Smith, G.E. Schwarz, and R.B. Alexander. Regional interpretation of water-quality monitoring data. Water Resources Research, 33:2781-2798, 1997.
97. D.G. Sprugel. Correcting for bias in log-transformed allometric equations. Ecology, 64(1):209-210, 1983.
98. R.J. Steidl, J.P. Hayes, and E. Schauber. Statistical power analysis in wildlife research. The Journal of Wildlife Management, 61(2):270-279, 1997.
99. C.A. Stow. Factors associated with PCB concentrations in Lake Michigan salmonids. Environmental Science and Technology, 29(2):522-527, 1995.
100. C.A. Stow and S.S. Qian. A size-based probabilistic assessment of PCB exposure from Lake Michigan fish consumption. Environmental Science and Technology, 32:2325-2330, 1998.
101. C.A. Stow, S.R. Carpenter, L.A. Eby, J.F. Amrhein, and R.J. Hesselberg. Evidence that PCBs are approaching stable concentrations in Lake Michigan fishes. Ecological Applications, 6(1):248-260, 1995.
102. C.A. Stow, E.C. Lamon, S.S. Qian, and C.S. Schrank. Will Lake Michigan lake trout meet the Great Lakes strategy 2002 PCB reduction goal? Environmental Science and Technology, 38(2):359-363, 2004.
103. C.A. Stow, K.H. Reckhow, and S.S. Qian. A Bayesian approach to retransformation bias in transformed regression. Ecology, 87(6):1472-1477, 2006.
104. Student. The probable error of a mean. Biometrika, 6(1):1-25, 1908.
105. D.C. Thiele, Chester E.T., Moore S.E., Sirovic A., Hildebrand J.A., and Friedlaender A.S. Seasonal variability in whale encounters in the western Antarctic Peninsula. Deep-Sea Research, 51:2311-2325, 2004.
106. J.W. Tukey. The future of data analysis. The Annals of Mathematical Statistics, 33(1):1-67, 1962. ISSN 00034851.
107. J.W. Tukey. Exploratory Data Analysis. Addison-Wesley, Reading, MA, 1977.
108. U.S. EPA. Nutrient criteria technical guidance manual: Lakes and reservoirs. Technical report, EPA-822-B00-001, Office of Water, Washington, DC, 2000.
109. R.A. Vollenweider. Scientific fundations of the eutrophication of lakes and flowing waters, with particular reference to nitrogen and phosphorus as factors in eutrophication. Technical report, Organization for Economic Cooperation and Development, Technical Report DAS/CSI/68.27. 250p., 1968.
110. S. Weisberg. Applied Linear Regression. Wiley, New York, third edition, 2005.
111. S.N. Wood. Generalized Additive Models: An Introduction with R. Chapman and Hall/CRC Press, 2006.