Results 221 to 230 of about 8,530 (262)

GLOBAL ASYMPTOTIC NORMALITY

Statistics & Risk Modeling, 1983
The author generalizes an approximation theorem of \textit{R. Michel} and \textit{J. Pfanzagl} [Metrika 16, 188-205 (1970; Zbl 0218.62023)] for parametric families of probability measures. He proves that a uniform version of \textit{L. LeCam's} [Proc. 3rd Berkeley Sympos. math. Statist.
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Asymptotic Normality of Scaling Functions

SIAM Journal on Mathematical Analysis, 2004
The properties of probability measures are investigated. It is shown that if \(m\) is a probability measure on \(R\) with finite first moment, then the solution of the scaling equation \[ \phi (x) = \int_{R} \alpha \phi (\alpha x - y)\,dm(y),\quad x \in {\mathbb R} , \] is also a probability measure with the scale \(\alpha > 1\).
Goodman, Timothy, Chen, Louis H. Y., Lee, S. L.   +2 more
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Local Asymptotic Normality

2000
The classical theory of asymptotics in statistics relies heavily on certain local quadratic approximations to the logarithms of likelihood ratios. Such approximations will be studied here but in a restricted framework.
Lucien Le Cam, Grace Lo Yang
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Asymptotic Normality of some Estimators

Calcutta Statistical Association Bulletin, 1981
This paper uses martingale central limit theorem and continuous mapping theorem to establish asymptotic normality of log-likelihood ratio process, maximum likelihood estimators and the posterior distributions. Illustrative examples are given.
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Asymptotic Normality of Autoregressive Processes

Acta Applicandae Mathematicae, 2009
Using an approximation method along with a central limit theorem for \(m\)-dependent random variables, this paper prove an asymptotic normality for autoregressive processes, and provide the central limit theorems of the least square estimate and the Yule-Walker estimate of the parameters of an autoregressive process.
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Asymptotically normal dynamical semigroups

Journal of Statistical Physics, 1987
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Asymptotic Normality—Global

1986
This chapter elaborates properties of a certain widely applicable method of construction of estimates. The general idea is that one provides oneself with a well behaved auxiliary estimate of the parameter and that, in the vicinity of the estimated value, one refines the estimate using techniques adapted to the local structure of the experiment.
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Locally Asymptotically Normal Families

1990
The classical theory of asymptotics in Statistics relies heavily on certain local quadratic approximations to the logarithms of likelihood ratios. Such approximations will be studied here but in a restricted framework.
Lucien Le Cam, Grace Lo Yang
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Bootstrap and asymptotic normality

1992
In this chapter consistency of bootstrap is compared with asymptotic normality. This is done for linear statistics of n i. i. d. observations. It is shown that bootstrap works asymptotically under the same assumptions as a normal approximation with estimated variance (Theorem 1).
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LOCAL ASYMPTOTIC NORMALITY OF TRUNCATION MODELS

Statistics & Risk Modeling, 1999
Summary: We consider iid random elements \(X_1, \dots, X_n\) with values in some measurable space \((S,{\mathcal B})\). Suppose that we are only interested in those observations among \(X_1, \dots, X_n\) which fall into some subset \(D\in {\mathcal B}\) having but a small probability of occurence.
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