LEADER 01133nam0-2200385li-450 001 990000167200203316 005 20180312154801.0 010 $a0-88318-712-4 035 $a0016720 035 $aUSA010016720 035 $a(ALEPH)000016720USA01 035 $a0016720 100 $a20001109d1992----km-y0itay0103----ba 101 0 $aeng 102 $aUS 200 1 $aPhysics of climate$fJosé P. Peixoto and Abraham H. Oort$gforeword by Edward N. Lorenz 210 $aNew York$cAmerican Institute of Physics$dcopyr. 1992 610 1 $aclimatologia 610 1 $afisica atmosferica 610 1 $ameteorologia 676 $a551.5$9. 700 1$aPeixoto,$bJosé P.$0502988 702 1$aLorenz,$bEdward N. 702 1$aOort,$bAbraham H. 801 $aSistema bibliotecario di Ateneo dell' Università di Salerno$gRICA 912 $a990000167200203316 951 $a551.5 PEI$b0002348 959 $aBK 969 $aTEC 979 $c19950728 979 $c20001110$lUSA01$h1712 979 $c20020403$lUSA01$h1624 979 $aPATRY$b90$c20040406$lUSA01$h1612 996 $aPhysics of climate$91489367 997 $aUNISA LEADER 01260nam a2200361 i 4500 001 991000818839707536 005 20020507174001.0 008 941003s1994 ||| ||| | eng 020 $a3540566185 035 $ab10761524-39ule_inst 035 $aLE01302787$9ExL 040 $aDip.to Matematica$beng 082 0 $a516.36 084 $aAMS 53-01 084 $aAMS 53A05 084 $aAMS 58A10 084 $aAMS 58Z05 084 $aAMS 70H 084 $aLC QA381.C2813 100 1 $aCarmo, Manfredo Perdigao : do$030396 245 10$aDifferential forms and applications /$cManfredo P. do Carmo 260 $aBerlin :$bSpringer-Verlag,$cc1994 300 $aviii, 118 p. ;$c24 cm. 490 0 $aUniversitext 500 $aIncludes bibliographical references and index. 500 $aTransl. of the Portuguese book: "Formas diferenciais e aplicoes" published by IMPA in 1971 650 4$aDifferential forms 907 $a.b10761524$b23-02-17$c28-06-02 912 $a991000818839707536 945 $aLE013 53-XX CAR12 (1994)$g1$i2013000017068$lle013$o-$pE0.00$q-$rl$s- $t0$u3$v0$w3$x0$y.i10856808$z28-06-02 996 $aDifferential forms and applications$9375944 997 $aUNISALENTO 998 $ale013$b01-01-94$cm$da $e-$feng$gxx $h0$i1 LEADER 06281nam 22004813 450 001 9910830302503321 005 20230804080253.0 010 $a1-119-89182-5 010 $a1-119-89180-9 010 $a1-119-89181-7 035 $a(MiAaPQ)EBC30671936 035 $a(Au-PeEL)EBL30671936 035 $a(OCoLC)1375661421 035 $a(OCoLC-P)1375661421 035 $a(CaSebORM)9781119891796 035 $a(EXLCZ)9927902418400041 100 $a20230804d2023 uy 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aM-Statistics $eOptimal Statistical Inference for a Small Sample 205 $a1st ed. 210 1$aNewark :$cJohn Wiley & Sons, Incorporated,$d2023. 210 4$d©2023. 215 $a1 online resource (243 pages) 311 08$aPrint version: Demidenko, Eugene M-Statistics Newark : John Wiley & Sons, Incorporated,c2023 9781119891796 327 $aCover -- Title Page -- Copyright -- Contents -- Preface -- Chapter 1 Limitations of classic statistics and motivation -- 1.1 Limitations of classic statistics -- 1.1.1 Mean -- 1.1.2 Unbiasedness -- 1.1.3 Limitations of equal?tail statistical inference -- 1.2 The rationale for a new statistical theory -- 1.3 Motivating example: normal variance -- 1.3.1 Confidence interval for the normal variance -- 1.3.2 Hypothesis testing for the variance -- 1.3.3 MC and MO estimators of the variance -- 1.3.4 Sample size determination for variance -- 1.4 Neyman?Pearson lemma and its extensions -- 1.4.1 Introduction -- 1.4.2 Two lemmas -- References -- Chapter 2 Maximum concentration statistics -- 2.1 Assumptions -- 2.2 Short confidence interval and MC estimator -- 2.3 Density level test -- 2.4 Efficiency and the sufficient statistic -- 2.5 Parameter is positive or belongs to a finite interval -- 2.5.1 Parameter is positive -- 2.5.2 Parameter belongs to a finite interval -- References -- Chapter 3 Mode statistics -- 3.1 Unbiased test -- 3.2 Unbiased CI and MO estimator -- 3.3 Cumulative information and the sufficient statistic -- References -- Chapter 4 P?value and duality -- 4.1 P?value for the double?sided hypothesis -- 4.1.1 General definition -- 4.1.2 P?value for normal variance -- 4.2 The overall powerful test -- 4.3 Duality: converting the CI into a hypothesis test -- 4.4 Bypassing assumptions -- 4.5 Overview -- References -- Chapter 5 M?statistics for major statistical parameters -- 5.1 Exact statistical inference for standard deviation -- 5.1.1 MC?statistics -- 5.1.2 MC?statistics on the log scale -- 5.1.3 MO?statistics -- 5.1.4 Computation of the p?value -- 5.2 Pareto distribution -- 5.2.1 Confidence intervals -- 5.2.2 Hypothesis testing -- 5.3 Coefficient of variation for lognormal distribution -- 5.4 Statistical testing for two variances. 327 $a5.4.1 Computation of the p?value -- 5.4.2 Optimal sample size -- 5.5 Inference for two?sample exponential distribution -- 5.5.1 Unbiased statistical test -- 5.5.2 Confidence intervals -- 5.5.3 The MC estimator of ? -- 5.6 Effect size and coefficient of variation -- 5.6.1 Effect size -- 5.6.2 Coefficient of variation -- 5.6.3 Double?sided hypothesis tests -- 5.6.4 Multivariate ES -- 5.7 Binomial probability -- 5.7.1 The MCL estimator -- 5.7.2 The MCL2 estimator -- 5.7.3 The MCL2 estimator of pn -- 5.7.4 Confidence interval on the double?log scale -- 5.7.5 Equal?tail and unbiased tests -- 5.8 Poisson rate -- 5.8.1 Two?sided short CI on the log scale -- 5.8.2 Two?sided tests and p?value -- 5.8.3 The MCL estimator of the rate parameter -- 5.9 Meta?analysis model -- 5.9.1 CI and MCL estimator -- 5.10 M?statistics for the correlation coefficient -- 5.10.1 MC and MO estimators -- 5.10.2 Equal?tail and unbiased tests -- 5.10.3 Power function and p?value -- 5.10.4 Confidence intervals -- 5.11 The square multiple correlation coefficient -- 5.11.1 Unbiased statistical test -- 5.11.2 Computation of p?value -- 5.11.3 Confidence intervals -- 5.11.4 The two?sided CI on the log scale -- 5.11.5 The MCL estimator -- 5.12 Coefficient of determination for linear model -- 5.12.1 CoD and multiple correlation coefficient -- 5.12.2 Unbiased test -- 5.12.3 The MCL estimator for CoD -- References -- Chapter 6 Multidimensional parameter -- 6.1 Density level test -- 6.2 Unbiased test -- 6.3 Confidence region dual to the DL test -- 6.4 Unbiased confidence region -- 6.5 Simultaneous inference for normal mean and standard deviation -- 6.5.1 Statistical test -- 6.5.2 Confidence region -- 6.6 Exact confidence inference for parameters of the beta distribution -- 6.6.1 Statistical tests -- 6.6.2 Confidence regions -- 6.7 Two?sample binomial probability -- 6.7.1 Hypothesis testing. 327 $a6.7.2 Confidence region -- 6.8 Exact and profile statistical inference for nonlinear regression -- 6.8.1 Statistical inference for the whole parameter -- 6.8.2 Statistical inference for an individual parameter of interest via profiling -- References -- Index -- EULA. 330 $a"M-statistics: A New Statistical Perspective introduces a new approach for statistical interference, redesigning the fundamentals of statistics and improving on the classical methods we already use. The author discusses the development of new criteria for efficient estimation and delves into how two methods for statistical intereference are combined under one umbrella to create 'M statistics.' This book develops novel confidence intervals and statistical tests for statistical parameters including effect size, binomial probability, and Poisson rate, ensuring unbiased tests are developed alongside this. Suitable for professionals and students alike, this theoretical book explains how new approaches work for statistical applications and is accompanied with a GitHub repository hosting the R code for every new methodology presented."--$cProvided by publisher. 606 $aMathematical statistics 615 0$aMathematical statistics. 676 $a519.5/4 700 $aDemidenko$b Eugene$01260816 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910830302503321 996 $aM-Statistics$94074566 997 $aUNINA