LEADER 00991nam0-2200349---450- 001 990009462440403321 005 20111103084139.0 010 $a978-0-387-88697-8 035 $a000946244 035 $aFED01000946244 035 $a(Aleph)000946244FED01 035 $a000946244 100 $a20111025d2009----km-y0itay50------ba 101 0 $aeng 102 $aUS 105 $aa-------001yy 200 1 $aIntroductory time series with R$fPaul S.P. Cowpertwait, Andrew V. Metcalfe 210 $aNew York$cSpringer$d2009 215 $axv, 254 p.$cill.$d24 cm 225 1 $aUse R! 610 0 $aSerie temporali$aAnalisi 610 0 $aR (linguaggio) 676 $a519.5$v21$zita 700 1$aCowpertwait,$bPaul S.P.$0513767 701 1$aMetcalfe,$bAndrew V.$0145015 801 0$aIT$bUNINA$gREICAT$2UNIMARC 901 $aBK 912 $a990009462440403321 952 $aVI E 1395$b48079$fFSPBC 959 $aFSPBC 996 $aIntroductory time series with R$9853521 997 $aUNINA LEADER 00923nam a2200241 i 4500 001 991002875359707536 008 021023s1978 it a b 001 0 ita d 035 $ab11721698-39ule_inst 040 $aBibl. Interfacoltà$bita 100 1 $aGarosi, Gino$0156246 245 10$aLetteratura italiana :$b storia e testi /$cGarosi Gino ; introduzione e note di Gabriele La Porta 260 $aFirenze:$bL.S. Olscki,$c1978 300 $a271 p. :$b ill. ; $c31 cm. 440 1$aI classici italiani ; $v 134 500 $aComprende bibliografia e indici. 650 4$aLetteratura italiana 700 1 $aLa Porta, Gabriele 907 $a.b11721698$b02-04-14$c23-10-02 912 $a991002875359707536 945 $aLE002 Lett. IV B 2$g1$iLE002-245678$lle002$o-$pE0.00$q-$rl$s- $t0$u0$v0$w0$x0$y.i11961466$z23-10-02 996 $aLetteratura italiana$9903920 997 $aUNISALENTO 998 $ale002$b23-10-02$cm$da $e-$fita$git $h0$i0 LEADER 05707nam 2200745Ia 450 001 9910141196803321 005 20200520144314.0 010 $a9786613622044 010 $a9781280592218 010 $a1280592214 010 $a9781118162767 010 $a1118162765 010 $a9781118162729 010 $a1118162722 010 $a9781118162781 010 $a1118162781 035 $a(CKB)2670000000133070 035 $a(EBL)818500 035 $a(OCoLC)779165198 035 $a(SSID)ssj0000664637 035 $a(PQKBManifestationID)11390339 035 $a(PQKBTitleCode)TC0000664637 035 $a(PQKBWorkID)10631371 035 $a(PQKB)11054083 035 $a(MiAaPQ)EBC818500 035 $a(Perlego)1012418 035 $a(EXLCZ)992670000000133070 100 $a20110816d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aStatistics for censored environmental data using Minitab and R /$fDennis R. Helsel 205 $a2nd ed. 210 $aHoboken, N.J. $cWiley$dc2012 215 $a1 online resource (347 p.) 225 1 $aWiley series in statistics in practice 300 $aDescription based upon print version of record. 311 08$a9780470479889 311 08$a0470479884 320 $aIncludes bibliographical references and index. 327 $aSTATISTICS FOR CENSORED ENVIRONMENTAL DATA USING MINITAB AND R; CONTENTS; Preface; Acknowledgments; Introduction to the First Edition: An Accident Waiting To Happen; Introduction to the Second Edition: Invasive Data; 1 Things People Do with Censored Data that Are Just Wrong; Why Not Substitute-Missing the Signals that Are Present in the Data; Why Not Substitute?-Finding Signals that Are Not There; So Why Not Substitute?; Other Common Misuses of Censored Data; 2 Three Approaches for Censored Data; Approach 1: Nonparametric Methods after Censoring at the Highest Reporting Limit 327 $aApproach 2: Maximum Likelihood EstimationApproach 3: Nonparametric Survival Analysis Methods; Application of Survival Analysis Methods to Environmental Data; Parallels to Uncensored Methods; 3 Reporting Limits; Limits When the Standard Deviation is Considered Constant; Insider Censoring-Biasing Interpretations; Reporting the Machine Readings of all Measurements; Limits When the Standard Deviation Changes with Concentration; For Further Study; 4 Reporting, Storing, and Using Censored Data; Reporting and Storing Censored Data; Using Interval-Censored Data; Exercises; 5 Plotting Censored Data 327 $aBoxplotsHistograms; Empirical Distribution Function; Survival Function Plots; Probability Plot; X-Y Scatterplots; Exercises; 6 Computing Summary Statistics and Totals; Nonparametric Methods after Censoring at the Highest Reporting Limit; Maximum Likelihood Estimation; The Nonparametric Kaplan-Meier and Turnbull Methods; ROS: A "Robust" Imputation Method; Methods in Excel; Handling Data with High Reporting Limits; A Review of Comparison Studies; Summing Data with Censored Observations; Exercises; 7 Computing Interval Estimates; Parametric Intervals; Nonparametric Intervals 327 $aIntervals for Censored Data by SubstitutionIntervals for Censored Data by Maximum Likelihood; Intervals for the Lognormal Distribution; Intervals Using "Robust" Parametric Methods; Nonparametric Intervals for Censored Data; Bootstrapped Intervals; For Further Study; Exercises; 8 What Can be Done When All Data Are Below the Reporting Limit?; Point Estimates; Probability of Exceeding the Reporting Limit; Exceedance Probability for a Standard Higher than the Reporting Limit; Hypothesis Tests Between Groups; Summary; Exercises; 9 Comparing Two Groups; Why Not Use Substitution? 327 $aSimple Nonparametric Methods After Censoring at the Highest Reporting LimitMaximum Likelihood Estimation; Nonparametric Methods; Value of the Information in Censored Observations; Interval-Censored Score Tests: Testing Data that Include (DL to RL) Values; Paired Observations; Summary of Two-Sample Tests for Censored Data; Exercises; 10 Comparing Three or More Groups; Substitution Does Not Work-Invasive Data; Nonparametric Methods after Censoring at the Highest Reporting Limit; Maximum Likelihood Estimation; Nonparametric Method-The Generalized Wilcoxon Test; Summary; Exercises; 11 Correlation 327 $aTypes of Correlation Coefficients 330 $a Praise for the First Edition "" . . . an excellent addition to an upper-level undergraduate course on environmental statistics, and . . . a 'must-have' desk reference for environmental practitioners dealing with censored datasets."" -Vadose Zone Journal Statistical Methods for Censored Environmental Data Using Minitab® and R, Second Edition introduces and explains methods for analyzing and interpreting censored data in the environmental sciences. Adapting survival analysis techniques from other fields, the book translates well-established methods from other disciplines into new solu 410 0$aStatistics in practice. 606 $aEnvironmental sciences$xStatistical methods 606 $aPollution$xMeasurement$xStatistical methods 606 $aR (Computer program language) 615 0$aEnvironmental sciences$xStatistical methods. 615 0$aPollution$xMeasurement$xStatistical methods. 615 0$aR (Computer program language) 676 $a363.730285/53 700 $aHelsel$b Dennis R$0924336 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910141196803321 996 $aStatistics for censored environmental data using Minitab and R$92074312 997 $aUNINA