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Local Optimality Criteria Based on Asymptotic Normality

2013
The approach considered in this chapter is probably the most common for designing experiments in nonlinear situations. It consists in optimizing a scalar function of the asymptotic covariance matrix of the estimator and thus relies on asymptotic normality, as considered in Chaps. 3 and 4. Design based on more accurate characterizations of the precision
Luc Pronzato, Andrej Pázman
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Local Asymptotic Normality of Families of Distributions

1981
In a number of interesting papers of Hajek, LeCam, and other authors, it was proved that many important properties of statistical estimators follow from the asymptotic normality of the logarithm of the likelihood ratio for neighborhood hypotheses (for values of parameters close to each other) regardless of the relation between the observations which ...
I. A. Ibragimov, R. Z. Has’minskii
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Local asymptotic normality for multivariate nonlinear AR processes

Stochastics and Stochastic Reports, 2002
In this paper, we establish local asymptotic normality (LAN) for the log-likelihood ratio of a class of multivariate nonlinear autoregressive processes generated by independent identically distributed (i.i.d.) random vectors. This result generalizes LAN for multivariate linear processes to multivariate nonlinear autoregressive processes.
Dejian Lai   +2 more
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Local asymptotic normality for autoregression with infinite order

Journal of Statistical Planning and Inference, 1990
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Local Asymptotic Mixed Normality of Log­Likelihood Based on Stopping Times

Calcutta Statistical Association Bulletin, 1988
[Formula: see text]
Basu, A. K., Bhattacharya, Debasis
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Local asymptotic normality for stationary sequences of observations

Journal of Soviet Mathematics, 1983
The property of local asymptotic normality is established for stationary sequences under certain assumptions.
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Local asymptotic normality and asymptotical minimax efficiency of the MLE under random censorship

Science in China Series A: Mathematics, 2000
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Wang, QH, Jing, Bing Yi
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Local asymptotic normality of families of Gaussian distributions

Journal of Soviet Mathematics, 1986
Let \(\{X_ t\}\) be a stationary Gaussian sequence with \(EX_ t=0\) and with a spectral density \(f_{\theta}(\lambda)\), where \(\theta\in \Theta\subset R_ p\). Denote \(P(n,f_{\theta})\) the Gaussian distribution of \(X_ 1,...,X_ n\). The author proves that under suitable conditions the family \(\{P(n,f_{\theta})\}\) is locally asymptotically normal ...
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Local asymptotic normality for the scale parameter of stable processes

Statistics & Probability Letters, 2003
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