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

- 319 Want to read
- 2 Currently reading

Published
**2000**
by Oldenbourg in München
.

Written in English

- Estimation theory.,
- Mathematical statistics.,
- Probability measures.

**Edition Notes**

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

Statement | by D. Plachky. |

Series | Supplement issue, Statistics & decisions -- no. 5, Statistics & decisions -- no. 5. |

Classifications | |
---|---|

LC Classifications | QA276.8 .P53 2000 |

The Physical Object | |

Pagination | v, 169 p. ; |

Number of Pages | 169 |

ID Numbers | |

Open Library | OL18814483M |

ISBN 10 | 3486642685 |

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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