00919nam--2200349---450-99000216601020331620041112111238.0000216601USA01000216601(ALEPH)000216601USA0100021660120041112d1960----km-y0itay0103----baitaIT||||||||001yy<<Il>> giudizio civile di cassazioneElio FazzalariMilanoGiuffré1960X, 215 p.25 cm20012001001-------2001Cassazione civile347.9FAZZALARI,Elio133050ITsalbcISBD990002166010203316IG IV h 0162534 G.IG IV hBKGIUSIAV71020041112USA011112Giudizio civile di Cassazione583050UNISA00987nam a22002771i 450099100414832970753620031005201634.0031111s1992 gw |||||||||||||||||ger 3150081912b12530426-39ule_instARCHE-056369ExLDip.to LingueitaA.t.i. Arché s.c.r.l. Pandora Sicilia s.r.l.832.6Kleist, Heinrich :von86899Penthesilea /Heinrich von Kleist ; von Hedwig Appelt ; Maximilian NuntzStuttgart :Reclam,1992159 p. ;15 cmJare universal-bibliothek ;125Appelt, HedwigNuntz, Maximilian.b1253042602-04-1413-11-03991004148329707536LE012 838.6 KLE 912012000215863le012-E0.00-l- 00000.i1297313013-11-03Penthesilea18323UNISALENTOle01213-11-03ma -gergw 0105512nam 22006974a 450 991102032090332120200520144314.09786610287628978128028762612802876249780470024744047002474797804700269770470026979(CKB)1000000000355614(EBL)242945(OCoLC)173349038(SSID)ssj0000148540(PQKBManifestationID)11177018(PQKBTitleCode)TC0000148540(PQKBWorkID)10224752(PQKB)11745906(MiAaPQ)EBC242945(PPN)151204241(Perlego)2759736(EXLCZ)99100000000035561420030724d2004 uy 0engur|n|---|||||txtccrEnvironmental statistics methods and applications /Vic BarnettChichester, West Sussex, England ;Hoboken, NJ J. Wileyc20041 online resource (318 p.)Wiley series in probability and statisticsDescription based upon print version of record.9780471489719 0471489719 Includes bibliographical references (p. [267]-284) and index.Environmental Statistics; Contents; Preface; Chapter 1 Introduction; 1.1 Tomorrow is too Late!; 1.2 Environmental Statistics; 1.3 Some Examples; 1.3.1 'Getting it all together'; 1.3.2 'In time and space'; 1.3.3 'Keep it simple'; 1.3.4 'How much can we take?'; 1.3.5 'Over the top'; 1.4 Fundamentals; 1.5 Bibliography; PART I EXTREMAL STRESSES: EXTREMES, OUTLIERS, ROBUSTNESS; Chapter 2 Ordering and Extremes: Applications, models, inference; 2.1 Ordering the Sample; 2.1.1 Order statistics; 2.2 Order-based Inference; 2.3 Extremes and Extremal Processes; 2.3.1 Practical study and empirical modelsgeneralized extreme-value distributions2.4 Peaks over Thresholds and the Generalized Pareto Distribution; Chapter 3 Outliers and Robustness; 3.1 What is an Outlier?; 3.2 Outlier Aims and Objectives; 3.3 Outlier-Generating Models; 3.3.1 Discordancy and models for outlier generation; 3.3.2 Tests of discordancy for specific distributions; 3.4 Multiple Outliers: Masking and Swamping; 3.5 Accommodation: Outlier-Robust Methods; 3.6 A Possible New Approach to Outliers; 3.7 Multivariate Outliers; 3.8 Detecting Multivariate Outliers; 3.8.1 Principles; 3.8.2 Informal methods; 3.9 Tests of Discordancy3.10 Accommodation3.11 Outliers in linear models; 3.12 Robustness in General; PART II COLLECTING ENVIRONMENTAL DATA: SAMPLING AND MONITORING; Chapter 4 Finite-Population Sampling; 4.1 A Probabilistic Sampling Scheme; 4.2 Simple Random Sampling; 4.2.1 Estimating the mean, X; 4.2.2 Estimating the variance, S(2); 4.2.3 Choice of sample size, n; 4.2.4 Estimating the population total, X(T); 4.2.5 Estimating a proportion, P; 4.3 Ratios and Ratio Estimators; 4.3.1 The estimation of a ratio; 4.3.2 Ratio estimator of a population total or mean; 4.4 Stratified (simple) Random Sampling4.4.1 Comparing the simple random sample mean and the stratified sample mean4.4.2 Choice of sample sizes; 4.4.3 Comparison of proportional allocation and optimum allocation; 4.4.4 Optimum allocation for estimating proportions; 4.5 Developments of Survey Sampling; Chapter 5 Inaccessible and Sensitive Data; 5.1 Encountered Data; 5.2 Length-Biased or Size-Biased Sampling and Weighted Distributions; 5.2.1 Weighted distribution methods; 5.3 Composite Sampling; 5.3.1 Attribute Sampling; 5.3.2 Continuous variables; 5.3.3 Estimating mean and variance; 5.4 Ranked-Set Sampling5.4.1 The ranked-set sample mean5.4.2 Optimal estimation; 5.4.3 Ranked-set sampling for normal and exponential distributions; 5.4.4 Imperfect ordering; Chapter 6 Sampling in the Wild; 6.1 Quadrat Sampling; 6.2 Recapture Sampling; 6.2.1 The Petersen and Chapman estimators; 6.2.2 Capture-recapture methods in open populations; 6.3 Transect Sampling; 6.3.1 The simplest case: strip transects; 6.3.2 Using a detectability function; 6.3.3 Estimating f (y); 6.3.4 Modifications of approach; 6.3.5 Point transects or variable circular plots; 6.4 Adaptive Sampling6.4.1 Simple models for adaptive samplingIn modern society, we are ever more aware of the environmental issues we face, whether these relate to global warming, depletion of rivers and oceans, despoliation of forests, pollution of land, poor air quality, environmental health issues, etc. At the most fundamental level it is necessary to monitor what is happening in the environment - collecting data to describe the changing scene. More importantly, it is crucial to formally describe the environment with sound and validated models, and to analyse and interpret the data we obtain in order to take action. Environmental Statistics Wiley series in probability and statistics.Mathematical statisticsEnvironmental sciencesStatistical methodsMathematical statistics.Environmental sciencesStatistical methods.519.5Barnett Vic12011MiAaPQMiAaPQMiAaPQBOOK9911020320903321Environmental statistics725980UNINA