LEADER 02700nam 2200589 450 001 996466671603316 005 20220908224144.0 010 $a3-540-37515-5 024 7 $a10.1007/BFb0096874 035 $a(CKB)1000000000438236 035 $a(SSID)ssj0000322884 035 $a(PQKBManifestationID)12091391 035 $a(PQKBTitleCode)TC0000322884 035 $a(PQKBWorkID)10289648 035 $a(PQKB)11406771 035 $a(DE-He213)978-3-540-37515-9 035 $a(MiAaPQ)EBC5585850 035 $a(Au-PeEL)EBL5585850 035 $a(OCoLC)1066184876 035 $a(MiAaPQ)EBC6842312 035 $a(Au-PeEL)EBL6842312 035 $a(OCoLC)793078398 035 $a(PPN)15521652X 035 $a(EXLCZ)991000000000438236 100 $a20220908d1976 uy 0 101 0 $aeng 135 $aurnn|008mamaa 181 $ctxt 182 $cc 183 $acr 200 00$aEmpirical distributions and processes $eselected papers from a meeting at Oberwolfach, March 28-April 3, 1976 /$fedited by P. Ga?nssler, P. Revesz 205 $a1st ed. 1976. 210 1$aBerlin, Germany :$cSpringer,$d[1976] 210 4$d©1976 215 $a1 online resource (VII, 150 p.) 225 1 $aLecture Notes in Mathematics,$x0075-8434 ;$v566 300 $aBibliographic Level Mode of Issuance: Monograph 311 $a3-540-08061-9 327 $aWeak approximations of the empirical process when parameters are estimated -- On the Erdös-Rényi increments and the P. Lévy modulus of continuity of a kiefer process -- Kolmogorov-smirnov tests when parameters are estimated -- On uniform convergence of measures with applications to uniform convergence of empirical distributions -- An alternative approach to glivenko-cantelli theorems -- Weak convergence under contiguous alternatives of the empirical process when parameters are estimated: The Dk approach -- Almost sure invariance principles for empirical distribution functions of weakly dependent random variables -- Three theorems of multivariate empirical process -- Weak convergence to stable laws by means of a weak invariance principle -- A necessary condition for the convergence of the isotrope discrepancy -- Two examples concerning uniform convergence of measures w.r.t. balls in Banach spaces. 410 0$aLecture Notes in Mathematics,$x0075-8434 ;$v566 606 $aRandom variables 615 0$aRandom variables. 676 $a519.2 702 $aRe?ve?sz$b Pa?l 702 $aGa?nssler$b Peter 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996466671603316 996 $aEmpirical distributions and processes$980714 997 $aUNISA