000 04091nam a22004335i 4500
001 978-1-4614-8456-1
003 DE-He213
005 20140220082831.0
007 cr nn 008mamaa
008 131016s2013 xxu| s |||| 0|eng d
020 _a9781461484561
_9978-1-4614-8456-1
024 7 _a10.1007/978-1-4614-8456-1
_2doi
050 4 _aQA276-280
072 7 _aUFM
_2bicssc
072 7 _aCOM077000
_2bisacsh
082 0 4 _a519.5
_223
100 1 _aMillard, Steven P.
_eauthor.
245 1 0 _aEnvStats
_h[electronic resource] :
_bAn R Package for Environmental Statistics /
_cby Steven P. Millard.
250 _a2nd ed. 2013.
264 1 _aNew York, NY :
_bSpringer New York :
_bImprint: Springer,
_c2013.
300 _aXVI, 291 p. 69 illus., 59 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPreface -- Chapters -- References -- Index.
520 _aThis book describes EnvStats, a new comprehensive R package for environmental statistics. EnvStats and R provide an open-source set of powerful functions for performing graphical and statistical analyses of environmental data, along with an extensive hypertext help system that explains what these methods do, how to use them, and where to find them in the environmental statistics literature. EnvStats also includes numerous built-in data sets from regulatory guidance documents, state and federal databases, and the literature. This book shows how to use EnvStats and R to easily: * Graphically display environmental data and probability distributions * Deal with non-detect (censored) data * Perform and plot results of goodness-of-fit tests * Compare chemical concentrations to a protection standard using confidence intervals for percentiles or parameters * Assess compliance at multiple sites for multiple constituents using simultaneous prediction limits * Test for trend accounting for seasons and serial correlation * Perform power and sample size computations with companion plots for sampling designs based on hypothesis tests, confidence intervals, prediction intervals, or tolerance intervals * Perform probabilistic risk assessment using Monte Carlo simulation * Reproduce specific examples in EPA guidance documents EnvStats combined with other R packages provide the environmental scientist, statistician, researcher, and technician with tools to “get the job done!” Steven P. Millard, Ph.D., is an independent statistical consultant and Senior Biostatistician at the VA Puget Sound Health Care System in Seattle, Washington, and has worked in the field of environmental and health care statistics for over 25 years. He has worked at the US Geological Survey, CH2M Hill, the University of California at Santa Barbara, Saint Martin’s College, Insightful Corporation, and the Cystic Fibrosis Therapeutics Development Network Coordinating Center. In 1990 he developed the training program in S-PLUS while at Statistical Sciences (the creator of S-PLUS), and later developed the S-PLUS module EnvironmentalStats for S-PLUS. He has taught numerous courses in statistics and software to professionals in the United States and Europe, including at the US EPA, Merck, and the National Security Agency. He is the co-author of textbooks on environmental statistics and statistics for drug development. Dr. Millard holds a B.A. in Mathematics from Pomona College, and an M.S. and Ph.D. in Biostatistics from the University of Washington.
650 0 _aStatistics.
650 0 _aMathematical statistics.
650 1 4 _aStatistics.
650 2 4 _aStatistics and Computing/Statistics Programs.
650 2 4 _aStatistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer eBooks
776 0 8 _iPrinted edition:
_z9781461484554
856 4 0 _uhttp://dx.doi.org/10.1007/978-1-4614-8456-1
912 _aZDB-2-SMA
999 _c96056
_d96056