Maximum likelihood estimators of clock offset and skew under exponential delays
نویسندگان
چکیده
منابع مشابه
Moderate Deviations of Maximum Likelihood Estimators under Alternatives
Since statistical models are simplifications of reality, it is important in estimation theory to study the behavior of estimators also under distributions (slightly) different from the proposed model. In testing theory, when dealing with test statistics where nuisance parameters are estimated, knowledge of the behavior of the estimators of the nuisance parameters is needed under alternatives to...
متن کاملAsymptotic Properties of Maximum Likelihood Estimators and Likelihood Ratio Tests Under Nonstandard Conditions
Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive o...
متن کاملMaximum likelihood estimation of skew t-copula
We construct a copula from the multivariate skew t-distribution of Azzalini and Capitanio (2003). This copula can capture asymmetric and extreme dependence between variables, and it is one of the few that is effective when the number of dimensions is high. However, two problems arise when estimating the parameters by maximum likelihood estimation. Here, we solve these problems and provide a con...
متن کاملClock offset estimation in wireless sensor networks using robust M-estimation
Clock synchronization plays a crucial role in Wireless Sensor Networks (WSNs). Assuming that there is no clock skew between sensor nodes, the Maximum Likelihood Estimate (MLE) of clock offset was derived by [1] for clock synchronization protocols assuming exponential random delays and a two-way message exchange mechanism as in TPSN (Timing-sync Protocol for Sensor Networks [2]) or NTP (Network ...
متن کاملThe Convergence of Lossy Maximum Likelihood Estimators
Given a sequence of observations (Xn)n≥1 and a family of probability distributions {Qθ}θ∈Θ, the lossy likelihood of a particular distribution Qθ given the data Xn 1 := (X1,X2, . . . ,Xn) is defined as Qθ(B(X 1 ,D)), where B(Xn 1 ,D) is the distortion-ball of radius D around the source sequence X n 1 . Here we investigate the convergence of maximizers of the lossy likelihood.
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Applied Stochastic Models in Business and Industry
سال: 2009
ISSN: 1524-1904,1526-4025
DOI: 10.1002/asmb.791