Daidzein
发表于 2025-3-21 18:29:03
书目名称Information Bounds and Nonparametric Maximum Likelihood Estimation影响因子(影响力)<br> http://impactfactor.cn/if/?ISSN=BK0465002<br><br> <br><br>书目名称Information Bounds and Nonparametric Maximum Likelihood Estimation影响因子(影响力)学科排名<br> http://impactfactor.cn/ifr/?ISSN=BK0465002<br><br> <br><br>书目名称Information Bounds and Nonparametric Maximum Likelihood Estimation网络公开度<br> http://impactfactor.cn/at/?ISSN=BK0465002<br><br> <br><br>书目名称Information Bounds and Nonparametric Maximum Likelihood Estimation网络公开度学科排名<br> http://impactfactor.cn/atr/?ISSN=BK0465002<br><br> <br><br>书目名称Information Bounds and Nonparametric Maximum Likelihood Estimation被引频次<br> http://impactfactor.cn/tc/?ISSN=BK0465002<br><br> <br><br>书目名称Information Bounds and Nonparametric Maximum Likelihood Estimation被引频次学科排名<br> http://impactfactor.cn/tcr/?ISSN=BK0465002<br><br> <br><br>书目名称Information Bounds and Nonparametric Maximum Likelihood Estimation年度引用<br> http://impactfactor.cn/ii/?ISSN=BK0465002<br><br> <br><br>书目名称Information Bounds and Nonparametric Maximum Likelihood Estimation年度引用学科排名<br> http://impactfactor.cn/iir/?ISSN=BK0465002<br><br> <br><br>书目名称Information Bounds and Nonparametric Maximum Likelihood Estimation读者反馈<br> http://impactfactor.cn/5y/?ISSN=BK0465002<br><br> <br><br>书目名称Information Bounds and Nonparametric Maximum Likelihood Estimation读者反馈学科排名<br> http://impactfactor.cn/5yr/?ISSN=BK0465002<br><br> <br><br>
虚弱
发表于 2025-3-21 23:07:02
Convolution and Asymptotic Minimax TheoremsNow we give statements of several convolution and asymptotic minimax theorems. The key hypotheses involved in virtually all the different formulations of these theorems are:
短程旅游
发表于 2025-3-22 02:32:18
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fulcrum
发表于 2025-3-22 07:41:38
ConsistencyConsistency of the NPMLE in the cases of interval censoring and deconvolution can be proved by a general method which has been used by Jewell (1982) in proving consistency of the NPMLE for the mixing distribution in scale mixtures of exponential distributions. We first illustrate the method for interval censoring, case 1.
蚀刻
发表于 2025-3-22 11:18:50
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conformity
发表于 2025-3-22 13:44:12
https://doi.org/10.1007/978-3-0348-8621-5Censoring; Estimator; Finite; Likelihood; Random variable; Variable; expectation–maximization algorithm; fu
可以任性
发表于 2025-3-22 21:06:01
Oberwolfach Seminarshttp://image.papertrans.cn/i/image/465002.jpg
Encapsulate
发表于 2025-3-23 00:57:21
978-3-7643-2794-1Springer Basel AG 1992
Factorable
发表于 2025-3-23 04:56:10
Information Bounds and Nonparametric Maximum Likelihood Estimation978-3-0348-8621-5Series ISSN 1661-237X Series E-ISSN 2296-5041
飞来飞去真休
发表于 2025-3-23 06:54:42
Van der Vaart’s Differentiability Theoremhen we want to estimate certain functionals of the underlying parameter. For example, in example 1.1.3 we may want to estimate the mean of ., or . at a single point .. Thus, in terms of the distribution . = . of the observed data, we want to estimate the implicitly defined functional . where . is the mean of . or .(.).