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Bayes,Jeffreys,Prior Distributions and the Philosophy of Statistics
Bayes Jeffreys Prior Distributions Philosophy of Statistics
2010/3/9
I actually own a copy of Harold Jeffreys’s The-
ory of Probability but have only read small bits of
it, most recently over a decade ago to confirm that,
indeed, Jeffreys was not too proud to use a ...
Edgeworth expansions for studentized statistics under weak dependence
Cramer’s condition linear process M-estimators smooth func-tion model spectral density estimator strong mixing
2010/3/9
In this paper, we derive valid Edgeworth expansions for studen-
tized versions of a large class of statistics when the data are generated
by a strongly mixing process. Under dependence, the asymptot...
On the information-theoretical foundations of quantum statistics
the information-theoretical foundations quantum statistics
2009/9/24
On the information-theoretical foundations of quantum statistics。
Consistency of tests in noncommutative statistics
Consistency tests in noncommutative statistics
2009/9/23
The paper investigates noncommutative sequential
tests. There are defined consistency and uniform consistency of such.
tests, and then sufficient and necessary conditions-for the test to be
consist...
Characterisations of the geometric distribution using distributional properties of the order statistics
the geometric distribution distributional properties the order statistics
2009/9/23
Characterisations of the geometric distribution using distributional properties of the order statistics。
On a limit theorem and invariance principle for symmetric statistics
a limit theorem invariance principle symmetric statistics
2009/9/23
On a limit theorem and invariance principle for symmetric statistics。
The domain of attraction of stable laws and extreme order statistics
domain of attraction stable laws extreme order statistics
2009/9/23
The domain of attraction of stable laws and extreme order statistics。
U-functions of concomitants of order statistics。
Edgeworth expansions and bootstrap for degenerate von Mises statistics
Edgeworth expansions bootstrap for degenerate Mises statistics
2009/9/22
We prove Edgeworth expansions for degenerate von
Mises statistics like the Beran, Watson, and Cram&-von Mises
goodness-of-fit statistics. Furthermore, we show that the bootstrap
approximation works...
In the classical approach to pseudorandom number
generators, a generator is considered to perform well if its output
sequences pass a battery of statistical tests that has h o m e standard.
In rece...
Asymptotic theory of linear statistics in sampling proportional to size without replacement
Asymptotic theory of linear statistics sampling proportional size without replacement
2009/9/22
Consider an ordered sample that is selected from
a finite population successively without replacement and with probability
proportional to some measure of size. In this paper, we study the
asymptot...
Cryptography, statistics and pseudorandomness. II
Cryptography statistics pseudorandomness
2009/9/22
This paper is a sequel to Brands and Gill [5] which
contained an introduction to the cryptographic theory of random
number generation. Here we give a detailed analysis of the
QR-generator.
Bayesian inference is one of the more controversial approaches to
statistics. The fundamental objections to Bayesian methods are twofold: on one
hand, Bayesian methods are presented as an automatic ...
Edgeworth expansions for L-statistics
Linear combinations of order statistics Edgeworth cxpanaions rate of convergence
2009/9/21
We study the appraxhatioa by a short mgeworth
expmdon of the distribution functian of no
of order sratistim of n indewdent random vitriabIes with common
diswibutian fmction F. Under the wumptians
...
Limit theorems for arrays of maximal order statistics
Almost sure convergence weak law of large numbers generalized law of the iterated logarithm
2009/9/21
Let {x, Xd, 1 d j d m., n 3 1) be independent and
identically distributed random variables with the Pareto distribution.
Let X,,, be the k-th largest order statistic from the n-th row of our
array....