典型文献
Asymptotic in the Ordered Networks with a Noisy Degree Sequence
文献摘要：
In the case of the differential privacy under the Laplace mechanism,the asymptotic prop-erties of parameter estimators have been derived in some special network models with common binary values,but the asymptotic properties in network models with the ordered values are lacking.In this pa-per,the authors release the degree sequences of the ordered networks under a general noisy mechanism with the discrete Laplace mechanism as a special case.The authors establish the asymptotic result including the consistency and asymptotical normality of the parameter estimator when the number of parameters goes to infinity.Simulations and a real data example are provided to illustrate asymptotic results.
文献关键词：
中图分类号：
作者姓名：
LUO Jing;QIN Hong
作者机构：
Department of Mathematics and Statistics,South-Central University for Nationalities,Wuhan 430074,China;Department of Statistics,Zhongnan University of Economics and Law,Wuhan 430073,China
文献出处：
引用格式：
[1]LUO Jing;QIN Hong-.Asymptotic in the Ordered Networks with a Noisy Degree Sequence)[J].系统科学与复杂性学报（英文版）,2022(03):1137-1153
A类：
asymptotical
B类：
Asymptotic,Ordered,Networks,Noisy,Degree,Sequence,In,case,differential,privacy,under,Laplace,mechanism,estimators,have,been,derived,some,special,models,common,binary,values,but,properties,ordered,are,lacking,this,authors,release,degree,sequences,networks,general,noisy,discrete,establish,including,consistency,normality,when,number,parameters,goes,infinity,Simulations,real,data,example,provided,illustrate,results
AB值：
0.553161
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