A minimum average risk approach to shrinkage estimators of the normal mean

For the problem of estimating the normal mean based on a random sample X ₁,...,X _n when a prior value ₀ is available, a class of shrinkage estimators % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqdbaGafqiVd0MbaKaaaaGccaqGGaGaaiikaiaa% dUgacaGGPaGaeyypa0Jaam4AaiaacIcadaqfqaqabKqaahaacaqGUb% aaleqaneaacaqGubaaaOGaaiykaiaabccadaqfqaqabKqaahaacaWG% UbaaleqaneaaceqGybGbaebaaaGccaqGGaGaey4kaSIaaeiiaiaacI% cacaaIXaGaaeiiaiabgkHiTiaabccacaWGRbGaaiikamaavababeqc% baCaaiaab6gaaSqab0qaaiaabsfaaaGccaGGPaGaaiykamaavababe% qcbaCaaiaad6gaaSqab0qaaiabeY7aTbaaaaa!5615!\[\mathop {\hat \mu }\nolimits_n {\rm{ }}(k) = k(\mathop {\rm{T}}\nolimits_{\rm{n}} ){\rm{ }}\mathop {{\rm{\bar X}}}\nolimits_n {\rm{ }} + {\rm{ }}(1{\rm{ }} - {\rm{ }}k(\mathop {\rm{T}}\nolimits_{\rm{n}} ))\mathop \mu \nolimits_n \] is considered, where % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqcdawaaiaadsfaaaGccaqGGaGaaeypaiaabcca% caWGUbWaaWbaaSqabeaacaaIXaGaai4laiaaikdaaaGccaGGOaWaa0% aaaeaacaWGybaaamaaBaaajeaWbaGaamOBaaWcbeaakiaabccacqGH% sislcaqGGaWaaubeaeqajeaWbaGaaGimaaWcbeqdbaGaaeiVdaaaki% aacMcacaqGGaGaae4laiabeccaGiabeo8aZbaa!4C33!\[\mathop T\nolimits_n {\rm{ = }}n^{1/2} (\overline X _n {\rm{ }} - {\rm{ }}\mathop {\rm{\mu }}\nolimits_0 ){\rm{ /}} \sigma \] and k is a weight function. For certain choices of k, % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqdbaGafqiVd0MbaKaaaaGccaqGGaGaaiikaiaa% dUgacaGGPaaaaa!3CEE!\[\mathop {\hat \mu }\nolimits_n {\rm{ }}(k)\] coincides with previously studied preliminary test and shrinkage estimators. We consider choosing k from a natural non-parametric family of weight functions so as to minimize average risk relative to a specified prior p. We study how, by varying p, the MSE efficiency (relative to \-X) properties of % MathType!MTEF!2!1!+-% feaafeart1ev1aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn% hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr% 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9% vqaqpepm0xbba9pwe9Q8fs0-qqaqpepae9pg0FirpepeKkFr0xfr-x% fr-xHapdbiqaaeGaciGaaiaabeqaamaabaabaaGcbaWaaubeaeqaje% aWbaGaamOBaaWcbeqdbaGafqiVd0MbaKaaaaGccaqGGaGaaiikaiaa% dUgacaGGPaaaaa!3CEE!\[\mathop {\hat \mu }\nolimits_n {\rm{ }}(k)\] can be controlled. In the process, a certain robustness property of the usual family of posterior mean estimators, corresponding to the conjugate normal priors, is observed.     

Na2SnO3系催化剂在甲烷氧化偶联反应中的催化性能及表面碱性的探讨

1982年Keller和Bhasin以金属氧化物为催化剂从甲烷制得少量乙烯和乙烷的工作引起了各国研究工作者的重视,此后报道了许多有研究价值的催化剂,其中添加碱金属对提高催化性能所起的作用引起了普遍的关注.Lunsford等首先用添加Li~+的MgO作催化剂,发现催化剂表面碱性增强的同时,生成C_2烃类产物的选择性明显增加.随后Iwamatu等在MgO中添加Na~+及Rb~+盐,Jones等在Mn~(4+)/SiO_2中添加Na~+,Otsuka等在Sm_2O_3中添加LiCl作为甲烷氧化偶联催化剂进行了研究,这些结果均表明,因添加碱金属使催化剂呈现     

四苯基卟啉及其衍生物的表面光电压谱

酞菁和卟啉染料是一类典型的分子半导体材料,由于其在生命过程、癌的治疗等生物学上的探索及其化学传感、光电特性在固体电子学器件研究中占有很重要的地位。尤以这类染料的光电性质深受人们的重视,这与太阳能光电池、光MOS晶体管等的应用前景是分     

多功能沸点仪的研究

本文提出了两种新型沸点仪——CP-Ⅰ型和CP-Ⅱ型沸点仪, 阐述了仪器各部分结构的设计思想和原理, 并对仪器的性能和各部分功能进行了较为完整的实验考核, 获得了预期的效果。     

Kinetics of uranium(VI) extraction by bis(octylsulfinyl)methane

The kinetics and mechanism of uranium(VI) extraction from nitric acid solution by bis(octylsulfinyl)methane (BOSM) are studied with the method of stationary interface cell. The effects of temperature, extractant and nitric acid concentrations are discussed. The results showed that the extraction process is controlled by the following reaction: UO₂(NO₃)₂ + BOSM_(i)⇄_k1 ^k-1UO₂(NO₃)₂BOSM_(i). The variation of enthalpy associated with the extraction is -22.1±2.1 kJ/mol. This revised version was published online in July 2006 with corrections to the Cover Date.     

长光路光度法测定中药材中痕量硒

本文研究了用长光路光度法测定痕量硒。在酸性溶液中，Ｓｅ（Ⅳ）催化ＫＣｌＯ３氧化苯肼成偶氮离子，继而与变色酸生成红色偶氮化合物。硒含量在１．０×１０－９～２．０×１０－７ｇ／ｍＬ范围内遵守比尔定律。巯基棉分离后，测定中药材中总硒，获得满意结果。