From the reviews: "Baayen's book must surely in the future become the standard point of departure for statistical studies of vocabulary." (Geoffrey Sampson (Computational Linguistics, 28:04)

• 1 Word Frequencies.- 1.1 Introduction.- 1.2 The frequency spectrum.- 1.3 Zipf.- 1.4 The quest for characteristic constants.- 1.5 The lognormal distribution.- 1.6 Discussion.- 1.7 Bibliographical Comments.- 1.8 Questions.- 2 Non-parametric models.- 2.1 Basic concepts.- 2.2 The Urn model.- 2.3 The Structural Type Distribution.- 2.4 The LNRE zone.- 2.5 Good-Turing estimates.- 2.6 Interpolation and Extrapolation.- 2.7 Discussion.- 2.8 Bibliographical Comments.- 2.9 Questions.- 3 Parametric models.- 3.1 Introduction.- 3.2 LNRE models.- 3.3 Evaluating Goodness of Fit.- 3.4 Parameter estimation.- 3.5 A comparative study.- 3.6 Comparing Lexical Measures Across Texts.- 3.7 Discussion.- 3.8 Bibliographical Comments.- 3.9 Questions.- 4 Mixture distributions.- 4.1 Introduction.- 4.2 Expectations, variances, and covariances.- 4.3 Examples of mixture distributions.- 4.4 Morphological Productivity.- 4.5 Discussion.- 4.6 Bibliographical Comments.- 4.7 Questions.- 5 The Randomness Assumption.- 5.1 The Randomness Assumption.- 5.2 Adjusted LNRE models.- 5.3 Discussion.- 5.4 Bibliographical Comments.- 6 Examples of Applications.- 6.1 Distributional properties of the lexicon.- 6.2 Morphological productivity.- 6.3 Authorship and Style.- 6.4 Beyond word frequency distributions.- 6.5 Some practical guidelines.- A List of Symbols.- B Solutions to the exercises.- C Software.- D Data sets.

From the reviews: "Baayen's book must surely in the future become the standard point of departure for statistical studies of vocabulary." (Geoffrey Sampson (Computational Linguistics, 28:04)

• 1 Word Frequencies.- 1.1 Introduction.- 1.2 The frequency spectrum.- 1.3 Zipf.- 1.4 The quest for characteristic constants.- 1.5 The lognormal distribution.- 1.6 Discussion.- 1.7 Bibliographical Comments.- 1.8 Questions.- 2 Non-parametric models.- 2.1 Basic concepts.- 2.2 The Urn model.- 2.3 The Structural Type Distribution.- 2.4 The LNRE zone.- 2.5 Good-Turing estimates.- 2.6 Interpolation and Extrapolation.- 2.7 Discussion.- 2.8 Bibliographical Comments.- 2.9 Questions.- 3 Parametric models.- 3.1 Introduction.- 3.2 LNRE models.- 3.3 Evaluating Goodness of Fit.- 3.4 Parameter estimation.- 3.5 A comparative study.- 3.6 Comparing Lexical Measures Across Texts.- 3.7 Discussion.- 3.8 Bibliographical Comments.- 3.9 Questions.- 4 Mixture distributions.- 4.1 Introduction.- 4.2 Expectations, variances, and covariances.- 4.3 Examples of mixture distributions.- 4.4 Morphological Productivity.- 4.5 Discussion.- 4.6 Bibliographical Comments.- 4.7 Questions.- 5 The Randomness Assumption.- 5.1 The Randomness Assumption.- 5.2 Adjusted LNRE models.- 5.3 Discussion.- 5.4 Bibliographical Comments.- 6 Examples of Applications.- 6.1 Distributional properties of the lexicon.- 6.2 Morphological productivity.- 6.3 Authorship and Style.- 6.4 Beyond word frequency distributions.- 6.5 Some practical guidelines.- A List of Symbols.- B Solutions to the exercises.- C Software.- D Data sets.

From the reviews: "Baayen's book must surely in the future become the standard point of departure for statistical studies of vocabulary." (Geoffrey Sampson (Computational Linguistics, 28:04)

• 1 Word Frequencies.- 1.1 Introduction.- 1.2 The frequency spectrum.- 1.3 Zipf.- 1.4 The quest for characteristic constants.- 1.5 The lognormal distribution.- 1.6 Discussion.- 1.7 Bibliographical Comments.- 1.8 Questions.- 2 Non-parametric models.- 2.1 Basic concepts.- 2.2 The Urn model.- 2.3 The Structural Type Distribution.- 2.4 The LNRE zone.- 2.5 Good-Turing estimates.- 2.6 Interpolation and Extrapolation.- 2.7 Discussion.- 2.8 Bibliographical Comments.- 2.9 Questions.- 3 Parametric models.- 3.1 Introduction.- 3.2 LNRE models.- 3.3 Evaluating Goodness of Fit.- 3.4 Parameter estimation.- 3.5 A comparative study.- 3.6 Comparing Lexical Measures Across Texts.- 3.7 Discussion.- 3.8 Bibliographical Comments.- 3.9 Questions.- 4 Mixture distributions.- 4.1 Introduction.- 4.2 Expectations, variances, and covariances.- 4.3 Examples of mixture distributions.- 4.4 Morphological Productivity.- 4.5 Discussion.- 4.6 Bibliographical Comments.- 4.7 Questions.- 5 The Randomness Assumption.- 5.1 The Randomness Assumption.- 5.2 Adjusted LNRE models.- 5.3 Discussion.- 5.4 Bibliographical Comments.- 6 Examples of Applications.- 6.1 Distributional properties of the lexicon.- 6.2 Morphological productivity.- 6.3 Authorship and Style.- 6.4 Beyond word frequency distributions.- 6.5 Some practical guidelines.- A List of Symbols.- B Solutions to the exercises.- C Software.- D Data sets.