John Benjamins Publishing Company
Chapter 12. Probabilistic multifactorial grammar and lexicology
Abstract
In this chapter you will learn how to model the speaker’s choice between two near synonymous words or constructions on the basis of contextual features. The most popular statistical tool that is used to create such models is logistic regression. The approach is illustrated by a case study of two Dutch causative auxiliaries. As in the case of linear regression, you will learn how to create, test and interpret a logistic model with the help of different R tools.
Abstract
In this chapter you will learn how to model the speaker’s choice between two near synonymous words or constructions on the basis of contextual features. The most popular statistical tool that is used to create such models is logistic regression. The approach is illustrated by a case study of two Dutch causative auxiliaries. As in the case of linear regression, you will learn how to create, test and interpret a logistic model with the help of different R tools.
Chapters in this book
- Prelim pages i
- Table of contents vii
- Acknowledgements xi
- Introduction 1
- Chapter 1. What is statistics? 7
- Chapter 2. Introduction to R 21
- Chapter 3. Descriptive statistics for quantitative variables 41
- Chapter 4. How to explore qualitative variables 69
- Chapter 5. Comparing two groups 87
- Chapter 6. Relationships between two quantitative variables 115
- Chapter 7. More on frequencies and reaction times 139
- Chapter 8. Finding differences between several groups 171
- Chapter 9. Measuring associations between two categorical variables 199
- Chapter 10. Association measures 223
- Chapter 11. Geographic variation of quite: Distinctive collexeme analysis 241
- Chapter 12. Probabilistic multifactorial grammar and lexicology 253
- Chapter 13. Multinomial (polytomous) logistic regression models of three and more near synonyms 277
- Chapter 14. Conditional inference trees and random forests 291
- Chapter 15. Behavioural profiles, distance metrics and cluster analysis 301
- Chapter 16. Introduction to Semantic Vector Spaces 323
- Chapter 17. Language and space 333
- Chapter 18. Multidimensional analysis of register variation 351
- Chapter 19. Exemplars, categories, prototypes 367
- Chapter 20. Constructional change and motion charts 387
- Epilogue 395
- The most important R objects and basic operations with them 397
- Main plotting functions and graphical parameters in R 409
- References 425
- Subject Index 433
- Index of R functions and packages 441
Chapters in this book
- Prelim pages i
- Table of contents vii
- Acknowledgements xi
- Introduction 1
- Chapter 1. What is statistics? 7
- Chapter 2. Introduction to R 21
- Chapter 3. Descriptive statistics for quantitative variables 41
- Chapter 4. How to explore qualitative variables 69
- Chapter 5. Comparing two groups 87
- Chapter 6. Relationships between two quantitative variables 115
- Chapter 7. More on frequencies and reaction times 139
- Chapter 8. Finding differences between several groups 171
- Chapter 9. Measuring associations between two categorical variables 199
- Chapter 10. Association measures 223
- Chapter 11. Geographic variation of quite: Distinctive collexeme analysis 241
- Chapter 12. Probabilistic multifactorial grammar and lexicology 253
- Chapter 13. Multinomial (polytomous) logistic regression models of three and more near synonyms 277
- Chapter 14. Conditional inference trees and random forests 291
- Chapter 15. Behavioural profiles, distance metrics and cluster analysis 301
- Chapter 16. Introduction to Semantic Vector Spaces 323
- Chapter 17. Language and space 333
- Chapter 18. Multidimensional analysis of register variation 351
- Chapter 19. Exemplars, categories, prototypes 367
- Chapter 20. Constructional change and motion charts 387
- Epilogue 395
- The most important R objects and basic operations with them 397
- Main plotting functions and graphical parameters in R 409
- References 425
- Subject Index 433
- Index of R functions and packages 441