Retina
发表于 2025-3-21 18:42:02
书目名称Estimation in Semiparametric Models影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0315783<br><br> <br><br>书目名称Estimation in Semiparametric Models影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0315783<br><br> <br><br>书目名称Estimation in Semiparametric Models网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0315783<br><br> <br><br>书目名称Estimation in Semiparametric Models网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0315783<br><br> <br><br>书目名称Estimation in Semiparametric Models被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0315783<br><br> <br><br>书目名称Estimation in Semiparametric Models被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0315783<br><br> <br><br>书目名称Estimation in Semiparametric Models年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0315783<br><br> <br><br>书目名称Estimation in Semiparametric Models年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0315783<br><br> <br><br>书目名称Estimation in Semiparametric Models读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0315783<br><br> <br><br>书目名称Estimation in Semiparametric Models读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0315783<br><br> <br><br>
都相信我的话
发表于 2025-3-21 22:06:57
Power Electronics and Power Systems say {.}: ϑ ∈ Θ, one can usually do better by estimating ϑ first, say by ϑ.(.), and using ∫ . . .(.) (.) as an estimate for ∫ .(.). There is an “intermediate” range, where we know something about the unknown probability measure ., but less than parametric theory takes for granted.
阐明
发表于 2025-3-22 03:54:40
F.S. Porter,G.V. Brown,J. Cottames the following presentation more transparent. It is justified by the fact that the problem of estimating an .-dimensional functional simply is the problem of estimating its . (1-dimensional) components. (The essential point: componentwise as. efficiency implies joint as. efficiency. See I ., p. 159, Corollary 9.3.6.)
猜忌
发表于 2025-3-22 05:09:10
Introduction say {.}: ϑ ∈ Θ, one can usually do better by estimating ϑ first, say by ϑ.(.), and using ∫ . . .(.) (.) as an estimate for ∫ .(.). There is an “intermediate” range, where we know something about the unknown probability measure ., but less than parametric theory takes for granted.
阴谋
发表于 2025-3-22 11:54:30
Tangent spaces and gradientses the following presentation more transparent. It is justified by the fact that the problem of estimating an .-dimensional functional simply is the problem of estimating its . (1-dimensional) components. (The essential point: componentwise as. efficiency implies joint as. efficiency. See I ., p. 159, Corollary 9.3.6.)
啤酒
发表于 2025-3-22 13:31:32
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啤酒
发表于 2025-3-22 17:08:13
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表主动
发表于 2025-3-22 23:37:05
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ANTI
发表于 2025-3-23 05:05:38
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Aggressive
发表于 2025-3-23 07:14:56
Refrigeration and Liquefaction,Equipped with the concepts of “tangent space” and “gradient” we now turn to the problem of estimating the functional К, based on an i.i.d. sample .,...,. generated by some . ∈ ..