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A New Fit Assessment Framework for Common Factor Models Using Generalized Residuals. [PDF]

Psychometrika
Sung Y, Han Y, Liu Y.
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ON ASYMPTOTICALLY NORMAL ESTIMATORS

, 1965
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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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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 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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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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Matching behaviour is asymptotically normal

Combinatorica, 1981
Ak-matching in a graphG is a set ofk edges, no two of which have a vertex in common. The number of these inG is writtenp(G, k). Using an idea due to L. H. Harper, we establish a condition under which these numbers are approximately normally distributed.
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On the asymptotic normality of self-normalized sums

Mathematical Proceedings of the Cambridge Philosophical Society, 1991
AbstractLet X1, …, Xn be a sequence of non-degenerate, symmetric, independent identically distributed random variables, and let Sn(rn) denote their sum when the rn largest in modulus have been removed. We obtain necessary and sufficient conditions for asymptotic normality of the studentized version of Sn(rn), and compare this to the condition for ...
Griffin, Philip S., Mason, David M.
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