The asymptotic normality of the fixed number of the maximum likelihood estimators(MLEs)in the directed finite weighted network models with an increasing bi-degree sequence has been established recently.In this article...The asymptotic normality of the fixed number of the maximum likelihood estimators(MLEs)in the directed finite weighted network models with an increasing bi-degree sequence has been established recently.In this article,we further derive the central limit theorem for linear combinations of all the MLEs with an increasing dimension when the edges take finite discrete weight.Simulation studies are provided to illustrate the asymptotic results.展开更多
The edges between vertices in networks take not only the common binary values, but also the ordered values in some situations(e.g., the measurement of the relationship between people from worst to best in social netwo...The edges between vertices in networks take not only the common binary values, but also the ordered values in some situations(e.g., the measurement of the relationship between people from worst to best in social networks). In this paper, the authors study the asymptotic property of the moment estimator based on the degrees of vertices in ordered networks whose edges are ordered random variables. In particular, the authors establish the uniform consistency and the asymptotic normality of the moment estimator when the number of parameters goes to infinity. Simulations and a real data example are provided to illustrate asymptotic results.展开更多
基金Luo's research is partially supported by the Fundamental Research Funds for the Central Universities(South-Central University for Nationalities(CZQ19010))National Natural Science Foundation of China(11801576)+2 种基金the Scientific Research Funds of South-Central University For Nationalities(YZZ17007)Qin's research is partially supported by National Natural Science Foundation of China(11871237)Wang's research is partially supported by the Fundamental Research Funds for the Central Universities(South-Central University for Nationalities(CZQ18017)).
文摘The asymptotic normality of the fixed number of the maximum likelihood estimators(MLEs)in the directed finite weighted network models with an increasing bi-degree sequence has been established recently.In this article,we further derive the central limit theorem for linear combinations of all the MLEs with an increasing dimension when the edges take finite discrete weight.Simulation studies are provided to illustrate the asymptotic results.
基金supported by the National Natural Science Foundation of China under Grant Nos.11271147,11471135partially supported by the National Natural Science Foundation of China under Grant No.11401239+1 种基金Funds of CCNU from the Colleges’s Basic Research and Operation of MOE(CCNU15A02032,CCNU15ZD011)a Fund from KLAS(130026507)
文摘The edges between vertices in networks take not only the common binary values, but also the ordered values in some situations(e.g., the measurement of the relationship between people from worst to best in social networks). In this paper, the authors study the asymptotic property of the moment estimator based on the degrees of vertices in ordered networks whose edges are ordered random variables. In particular, the authors establish the uniform consistency and the asymptotic normality of the moment estimator when the number of parameters goes to infinity. Simulations and a real data example are provided to illustrate asymptotic results.
