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Thursday, July 30, 2020 | History

2 edition of Extension of measures with applications to probability and statistics found in the catalog.

Extension of measures with applications to probability and statistics

Detlef Plachky

Extension of measures with applications to probability and statistics

by Detlef Plachky

  • 319 Want to read
  • 2 Currently reading

Published by Oldenbourg in München .
Written in English

    Subjects:
  • Estimation theory.,
  • Mathematical statistics.,
  • Probability measures.

  • Edition Notes

    Includes bibliographical references (p. 157-160) and index.

    Statementby D. Plachky.
    SeriesSupplement issue, Statistics & decisions -- no. 5, Statistics & decisions -- no. 5.
    Classifications
    LC ClassificationsQA276.8 .P53 2000
    The Physical Object
    Paginationv, 169 p. ;
    Number of Pages169
    ID Numbers
    Open LibraryOL18814483M
    ISBN 103486642685

    Extension of measure Sayan Mukherjee Dynkin’s ˇ theorem We will soon need to define probability measures on infinite and possible uncountable sets, like the power set of the naturals. This is hard. It is easier to define the measure on a much smaller collection of.   The second axiom of probability is that the probability of the entire sample space is one. Symbolically we write P (S) = 1. Implicit in this axiom is the notion that the sample space is everything possible for our probability experiment and .

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Clearly this $\sigma$-algebra is not complete, since $\{a\}$ and $\{b\}$ are $\mathbb{P}$-negligible, but not null. So, one complete extension could be the minimal one. But I don't see how can I build the other extension; in particular, I don't see how to construct a second probability measure to be an extension.

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