伟大 发表于 2025-3-26 21:54:51
Regenerative Cryogenic Refrigerators,s. In many cases, such e.s. are already available, and the role of the “local theory” is confined to establish their as. optimality. This is, in particular, the case if the tangent space is full, i.e. .(., .) = .(.). Then there exists one gradient only, hence any as. linear e.s. is necessarily as. e遍及 发表于 2025-3-27 03:33:16
http://reply.papertrans.cn/32/3158/315783/315783_32.png并入 发表于 2025-3-27 06:13:48
http://reply.papertrans.cn/32/3158/315783/315783_33.png闲聊 发表于 2025-3-27 11:23:44
http://reply.papertrans.cn/32/3158/315783/315783_34.png清澈 发表于 2025-3-27 13:53:17
Introductions known about ., then the sample mean is certainly the best estimator one can think of. If . is known to be the member of a certain parametric family, say {.}: ϑ ∈ Θ, one can usually do better by estimating ϑ first, say by ϑ.(.), and using ∫ . . .(.) (.) as an estimate for ∫ .(.). There is an “inter相反放置 发表于 2025-3-27 19:02:56
Tangent spaces and gradients a functional К. → ℝ, based on an i.i.d. sample (.,..., .), i.e. a realization from ., for some . ∈ .. The restriction to 1-dimensional functional makes the following presentation more transparent. It is justified by the fact that the problem of estimating an .-dimensional functional simply is the p厚颜 发表于 2025-3-27 22:38:22
http://reply.papertrans.cn/32/3158/315783/315783_37.png孤独无助 发表于 2025-3-28 05:11:01
http://reply.papertrans.cn/32/3158/315783/315783_38.png权宜之计 发表于 2025-3-28 09:57:00
http://reply.papertrans.cn/32/3158/315783/315783_39.png陈旧 发表于 2025-3-28 12:40:59
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