简介:考虑一般的分块半相依线性回归(SUR)模型及其相应的简约模型,给出简约模型下未知回归系数及其可估函数的协方差改进估计仍是分块SUR模型下相应参数的协方差改进估计的一个充要条件.
简介:AconstructiveproofisgivenfortheinversionformulaforzonalfunctionsonSL(2,R).AconcretelyconstructedsequenceofzonalfunctionsareprovedtosatisfytheinversionformulaobtaAnedbyHarish-Chandraforcompactsupportedinfinitelydifferentiablezonalfunctfons.Makinguseofthepropertyofthissequencesomehowsimilartothatofapproximationkernels,theauthorndeducethattheinversionformulaistrueforcontinuouszonalfunctiotmon8L(2,R)somecondition.Theclassicalresultcanbeviewedasacorollaryoftheresultshere.
简介:Theaimofthispaperistogiveasimpleproofoftherestrictiontheoremforthemaximaloperatorsonthed-dimensionalEuclideanspaceRd,whosetheoremwasprovedbyCarro-Rodriguezin2012.Moreover,weshallgivesomeremarksoftherestrictiontheoremforthelinearandthemultilinearoperatorsbyCarro-RodriguezandRodriguez,too.
简介:TwoLatinsquaresofordervarer-orthogonaliftheirsuperpositionproducesexactlyrdistinctorderedpairs.Thetwosquaresaresaidtober-orthogonalidempotentLatinsquaresanddenotedbyr-MOILS(v)iftheyareallidempotent.Inthispaper,weshowthatforanyintegerv≥28,thereexistsanr-MOILS(v)ifandonlyifr∈[v,v~2]\{v+1,v~2-1}.
简介:Inthispaper,wegetW1,p(Rn)-boundednessfortangentialmaximalfunc-tionandnontangentialmaximalfunction,whichimprovesJ.Kinnunen,P.LindqvistandTananka’sresults.
简介:LetDbeaboundedC3-domaininRdand(aij)beaboundedsymmetricmatrixdefinedonD.Considerthesymmetricform(u,v)=1/2∫Daij(x)(u(x))/(xi)(v(x))/(xj)dx,u,v∈H1(D).UndersomeassumptionsitisshownthatthediffusionprocessassociatedwiththeregularDirichletspace(,(H1(D))onL2(D)canbecharacterizedasauniquesolutionofacertainstochasticdifferentialequation.
简介:ThepapermodelsthearrivalofheterogeneousinformationduringR&DstagesasadoublystochasticPoissonprocess(DSPP).Thenewproductmarketintroductionisthoughtofasoptiononanoption(acompoundoption).ThispaperderivesananalyticapproximationvaluationformulafortheR&Doption,anddemonstratesthattheaccountsforheterogeneousinformationarrivalmayreducethepricingbiases.Thisway,thegapbetweenrealoptiontheoryandthepracticeofdecisionmakingwithrespecttoinvestmentinR&Disdiminished.