Limit Laws for Extreme Order Statistics Form Strong Mixing Processes
Limit Laws for Extreme Order Statistics Form Strong Mixing Processes
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In our eReader you can find the full English version of the book. Read Limit Laws for Extreme Order Statistics Form Strong Mixing Processes Online - link to read the book on full screen. Our eReader also allows you to upload and read Pdf, Txt, ePub and fb2 books. In the Mini eReder on the page below you can quickly view all pages of the book - Read Book Limit Laws for Extreme Order Statistics Form Strong Mixing Processes
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N — n n n n This method of constructing a strong-mixing sequence is due to Newell [6].
The limit law (2. 3) is not of the same form as H(x, y) and we conclude that by weakening the independence assumption a larger class of limit laws is possible. In the next section we prove a result which limits the size of this class.
10. 3. Possible Limit Laws .
Theorem 1 . Let ^ 1> be a stationary strong-mixing sequence.
If there exists a sequence of constants /a > 0, b :n > iN so that ^ n n — ' ^^"n - ^n^ ..."*" ^n' ^n - ^n^ "^ ^n^ ^^^ ^ limiting distribution, H(x, y), with G(x), the limiting distribution of P{M ^ 1) into k blocks of length m-q separated by blocks of length q. The fact that the blocks of length m-q are "nearly independent" because of the strong-mixing property is then used to obtain a functional equation for H(x, y).
What to read after Limit Laws for Extreme Order Statistics Form Strong Mixing Processes?
You can find similar books in the "Read Also" column, or choose other free books by Roy E Welsch to read onlineMoreLess
To quickly assess the difficulty of the text, read a short excerpt:
N — n n n n This method of constructing a strong-mixing sequence is due to Newell [6].
The limit law (2. 3) is not of the same form as H(x, y) and we conclude that by weakening the independence assumption a larger class of limit laws is possible. In the next section we prove a result which limits the size of this class.
10. 3. Possible Limit Laws .
Theorem 1 . Let ^ 1> be a stationary strong-mixing sequence.
If there exists a sequence of constants /a > 0, b :n > iN so that ^ n n — ' ^^"n - ^n^ ..."*" ^n' ^n - ^n^ "^ ^n^ ^^^ ^ limiting distribution, H(x, y), with G(x), the limiting distribution of P{M ^ 1) into k blocks of length m-q separated by blocks of length q. The fact that the blocks of length m-q are "nearly independent" because of the strong-mixing property is then used to obtain a functional equation for H(x, y).
What to read after Limit Laws for Extreme Order Statistics Form Strong Mixing Processes?
You can find similar books in the "Read Also" column, or choose other free books by Roy E Welsch to read onlineMoreLess
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