A central limit theorem for measurements on the logarithmic scale and its application to dimension estimates
Document type:
Zeitschriftenaufsatz
Author(s):
Denker, M. and Min, A.
Non-TUM Co-author(s):
ja
Cooperation:
national
Abstract:
We show consistency and asymptotic normality of certain estimators for expected exponential growth rates under i.i.d. observations. These statistical functionals are of the form T(F)=int(log(int(h(x,y)F(dx)))F(dy)) and are applicable to dimension estimates (information dimension), entropy estimates and estimations of the growth rate of generating functions. We also give an affirmative answer to a question posed by Keller in 1997 (A new estimator for information dimension with standard errors and confidence intervals, Stochastic Process. Appl. 71(2):187-206) whether this estimator, specialized for dimension, is an alternative to standard procedures.
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We show consistency and asymptotic normality of certain estimators for expected exponential growth rates under i.i.d. observations. These statistical functionals are of the form T(F)=int(log(int(h(x,y)F(dx)))F(dy)) and are applicable to dimension estimates (information dimension), entropy estimates and estimations of the growth rate of generating functions. We also give an affirmative answer to a question posed by Keller in 1997 (A new estimator for information dimension with standard errors and...
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