From Wikipedia, the free encyclopedia
Gauss窶適uzmin
Probability mass function
PDF of the Gauss Kuzmin Distribution
Cumulative distribution function
CDF of the Gauss Kuzmin Distribution
Parameters (none)
Support
PMF
CDF
Mean
Median
Mode
Variance
Skewness (not defined)
Excess kurtosis (not defined)
Entropy 3.432527514776... [1] [2] [3]

In mathematics, the Gauss窶適uzmin distribution is a discrete probability distribution that arises as the limit probability distribution of the coefficients in the continued fraction expansion of a random variable uniformly distributed in (0, 1). [4] The distribution is named after Carl Friedrich Gauss, who derived it around 1800, [5] and Rodion Kuzmin, who gave a bound on the rate of convergence in 1929. [6] [7] It is given by the probability mass function

Gauss–Kuzmin theorem

Let

be the continued fraction expansion of a random number x uniformly distributed in (0, 1). Then

Equivalently, let

then

tends to zero as n tends to infinity.

Rate of convergence

In 1928, Kuzmin gave the bound

In 1929, Paul Lテゥvy [8] improved it to

Later, Eduard Wirsing showed [9] that, for ホサ = 0.30366... (the Gauss窶適uzmin窶展irsing constant), the limit

exists for every s in [0, 1], and the function ホィ(s) is analytic and satisfies ホィ(0) = ホィ(1) = 0. Further bounds were proved by K. I. Babenko. [10]

See also

References

  1. ^ Blachman, N. (1984). "The continued fraction as an information source (Corresp.)". IEEE Transactions on Information Theory. 30 (4): 671窶674. doi: 10.1109/TIT.1984.1056924.
  2. ^ Kornerup, Peter; Matula, David W. (July 1995). "LCF: A Lexicographic Binary Representation of the Rationals". J.UCS the Journal of Universal Computer Science. Vol. 1. pp. 484窶503. CiteSeerX  10.1.1.108.5117. doi: 10.1007/978-3-642-80350-5_41. ISBN  978-3-642-80352-9. {{ cite book}}: |journal= ignored ( help)
  3. ^ Vepstas, L. (2008), Entropy of Continued Fractions (Gauss-Kuzmin Entropy) (PDF)
  4. ^ Weisstein, Eric W. "Gauss窶適uzmin Distribution". MathWorld.
  5. ^ Gauss, Johann Carl Friedrich. Werke Sammlung. Vol. 10/1. pp. 552窶556.
  6. ^ Kuzmin, R. O. (1928). "On a problem of Gauss". Dokl. Akad. Nauk SSSR: 375窶380.
  7. ^ Kuzmin, R. O. (1932). "On a problem of Gauss". Atti del Congresso Internazionale dei Matematici, Bologna. 6: 83窶89.
  8. ^ Lテゥvy, P. (1929). "Sur les lois de probabilitテゥ dont dテゥpendant les quotients complets et incomplets d'une fraction continue". Bulletin de la Sociテゥtテゥ Mathテゥmatique de France. 57: 178窶194. doi: 10.24033/bsmf.1150. JFM  55.0916.02.
  9. ^ Wirsing, E. (1974). "On the theorem of Gauss窶適usmin窶鏑テゥvy and a Frobenius-type theorem for function spaces". Acta Arithmetica. 24 (5): 507窶528. doi: 10.4064/aa-24-5-507-528.
  10. ^ Babenko, K. I. (1978). "On a problem of Gauss". Soviet Math. Dokl. 19: 136窶140.
From Wikipedia, the free encyclopedia
Gauss窶適uzmin
Probability mass function
PDF of the Gauss Kuzmin Distribution
Cumulative distribution function
CDF of the Gauss Kuzmin Distribution
Parameters (none)
Support
PMF
CDF
Mean
Median
Mode
Variance
Skewness (not defined)
Excess kurtosis (not defined)
Entropy 3.432527514776... [1] [2] [3]

In mathematics, the Gauss窶適uzmin distribution is a discrete probability distribution that arises as the limit probability distribution of the coefficients in the continued fraction expansion of a random variable uniformly distributed in (0, 1). [4] The distribution is named after Carl Friedrich Gauss, who derived it around 1800, [5] and Rodion Kuzmin, who gave a bound on the rate of convergence in 1929. [6] [7] It is given by the probability mass function

Gauss–Kuzmin theorem

Let

be the continued fraction expansion of a random number x uniformly distributed in (0, 1). Then

Equivalently, let

then

tends to zero as n tends to infinity.

Rate of convergence

In 1928, Kuzmin gave the bound

In 1929, Paul Lテゥvy [8] improved it to

Later, Eduard Wirsing showed [9] that, for ホサ = 0.30366... (the Gauss窶適uzmin窶展irsing constant), the limit

exists for every s in [0, 1], and the function ホィ(s) is analytic and satisfies ホィ(0) = ホィ(1) = 0. Further bounds were proved by K. I. Babenko. [10]

See also

References

  1. ^ Blachman, N. (1984). "The continued fraction as an information source (Corresp.)". IEEE Transactions on Information Theory. 30 (4): 671窶674. doi: 10.1109/TIT.1984.1056924.
  2. ^ Kornerup, Peter; Matula, David W. (July 1995). "LCF: A Lexicographic Binary Representation of the Rationals". J.UCS the Journal of Universal Computer Science. Vol. 1. pp. 484窶503. CiteSeerX  10.1.1.108.5117. doi: 10.1007/978-3-642-80350-5_41. ISBN  978-3-642-80352-9. {{ cite book}}: |journal= ignored ( help)
  3. ^ Vepstas, L. (2008), Entropy of Continued Fractions (Gauss-Kuzmin Entropy) (PDF)
  4. ^ Weisstein, Eric W. "Gauss窶適uzmin Distribution". MathWorld.
  5. ^ Gauss, Johann Carl Friedrich. Werke Sammlung. Vol. 10/1. pp. 552窶556.
  6. ^ Kuzmin, R. O. (1928). "On a problem of Gauss". Dokl. Akad. Nauk SSSR: 375窶380.
  7. ^ Kuzmin, R. O. (1932). "On a problem of Gauss". Atti del Congresso Internazionale dei Matematici, Bologna. 6: 83窶89.
  8. ^ Lテゥvy, P. (1929). "Sur les lois de probabilitテゥ dont dテゥpendant les quotients complets et incomplets d'une fraction continue". Bulletin de la Sociテゥtテゥ Mathテゥmatique de France. 57: 178窶194. doi: 10.24033/bsmf.1150. JFM  55.0916.02.
  9. ^ Wirsing, E. (1974). "On the theorem of Gauss窶適usmin窶鏑テゥvy and a Frobenius-type theorem for function spaces". Acta Arithmetica. 24 (5): 507窶528. doi: 10.4064/aa-24-5-507-528.
  10. ^ Babenko, K. I. (1978). "On a problem of Gauss". Soviet Math. Dokl. 19: 136窶140.

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