@article{debowski-glotto,
        title = {Zipf´s law against the text size: a half-rational model},
        author = {Lukasz Debowski},
        journal = {Glottometrics},
        pages = {49 - 60},
        volume = 4,
        year = 2002,
        biburl = {http://www.bibsonomy.org/bibtex/2b1267434d81756fd05da338b50b3d623/andreab},
	keywords = {zipf d4.1 entropy mandelbrot word frequency tagora glottometrics distribution doubleslope}
}

@article{kornai-glotto,
        title = {How many words are there?},
        author = {Andr\'as Kornai},
        journal = {Glottometrics},
        pages = {61 - 86},
        volume = 4,
        year = 2002,
        biburl = {http://www.bibsonomy.org/bibtex/25fda9b7aedb8eca6a970d0572beb9cac/andreab},
	keywords = {zipf d4.1 entropy mandelbrot word kornai frequency tagora glottometrics distribution doubleslope}
}

@article{montemurro-glotto,
        title = {Frequency-rank distribution of words in large text samples: phenomenology and models},
        author = {Marcelo A. Montemurro and D. Zanette},
        journal = {Glottometrics},
        pages = {87-99},
        volume = 4,
        year = 2002,
        biburl = {http://www.bibsonomy.org/bibtex/2ca52767c942af8778595d7182849a38b/andreab},
	keywords = {zipf d4.1 entropy mandelbrot word frequency tagora montemurro glottometrics distribution doubleslope}
}

@article{citeulike:686746,
        title = {Algorithmic information, complexity and Zipf's law},
        author = {V. K. Balasubrahmanyan and S. Naranan},
        journal = {Glottometrics},
        pages = {1--26},
        volume = 4,
        year = 2002,
        description = {CiteULike: Algorithmic information, complexity and Zipf's law},
	abstract = {Zipf’s law of word frequencies for language discourses is established with statistical rigor. Data show a departure from Zipf’s power law term at low frequencies. This is accounted by a modi-fying exponential term. Both arise naturally in a model for word frequencies based on Information Theory, algorithmic coding of a text preserving the symbol sequence, concepts from quantum statistical physics and computer science and extremum principles. The Optimum Meaning Preserving Code (OMPC) of the discourse is realized when word frequencies follow the Modified Power Law (MPL). The model predicts a variant of the MPL for the relative frequencies of a small fixed set of symbols such as letters, phonemes and grammatical words. The OMPC can be viewed as containing orderly and random parts. This leads us to a quantitative definition of complexity of a string (C) that tends to 0 for the extremes of ‘all order’ and ‘all random’ but is a maximum (C = 1) for a mixture of both (Gell-Mann). It is found that natural languages have maximum complexity. The uniqueness of Zipf’s power law index (γ = 2) is shown to arise in four different ways, one of which depends on scale invariance characteristic of fractal structures. It is argued that random text models are unsuitable for natural languages. It is speculated that a drastic change in symbol frequency distribution starting from phrases is related to emergence of meaning and coherence of a discourse.},
	biburl = {http://www.bibsonomy.org/bibtex/281af3604a0d101b67169733d5c8f67b8/andreab},
	keywords = {zipf d4.1 entropy mandelbrot word frequency tagora glottometrics distribution}
}

@article{vito2005,
        title = {Can simple models explain Zipf's law for all exponents?},
        author = {Ramon Ferrer i Cancho and Vito D.P.Servedio},
        journal = {Glottometrics},
        pages = {1-8},
        volume = 11,
        year = 2005,
        abstract = {H. Simon proposed a simple stochastic process for explaining Zipf’s law for word
frequencies. Here we introduce two similar generalizations of Simon’s model that cover the same
range of exponents as the standard Simon model. The mathematical approach followed minimizes the
amount of mathematical background needed for deriving the exponent, compared to previous
approaches to the standard Simon’s model. Reviewing what is known from other simple explanations
of Zipf’s law, we conclude there is no single radically simple explanation covering the whole range of
variation of the exponent of Zipf’s law in humans. The meaningfulness of Zipf’s law for word
frequencies remains an open question.
},
	biburl = {http://www.bibsonomy.org/bibtex/2e33a94a50df2557c8dade8b77ee76e21/vitelot},
	keywords = {zipf glottometrics ramon}
}