Statsmodels API
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Table of Contents

  • 1. statsmodels.api
  • 2. Basic Documentation
  • 3. Main modules of interest
  • 4. Other modules of interest
  • 5. statsmodel.sandbox
  • 6. statsmodel.sandbox2
  • 7. From official doc
    • 7.1. Linear Regression
    • 7.2. Generalized Linear Models
      • 7.2.1. Examples
      • 7.2.2. Technical Documentation
      • 7.2.3. Module Reference
        • 7.2.3.1. Model Class
        • 7.2.3.2. Results Class
        • 7.2.3.3. Families
        • 7.2.3.4. Link Functions
    • 7.3. Generalized Estimating Equations
    • 7.4. Robust Linear Models
    • 7.5. Linear Mixed Effects Models
    • 7.6. Regression with Discrete Dependent Variable
    • 7.7. ANOVA
    • 7.8. Time Series analysis tsa
    • 7.9. Models for Survival and Duration Analysis
    • 7.10. Statistics stats
    • 7.11. Nonparametric Methods nonparametric
    • 7.12. Generalized Method of Moments gmm
    • 7.13. Empirical Likelihood emplike
    • 7.14. Other Models miscmodels
    • 7.15. Distributions
    • 7.16. Graphics
    • 7.17. Input-Output iolib
    • 7.18. Tools
    • 7.19. The Datasets Package
    • 7.20. Sandbox
Statsmodels API
  • Docs »
  • 7. From official doc »
  • 7.2. Generalized Linear Models »
  • 7.2.3.4.6. statsmodels.genmod.families.links.NegativeBinomial
  • View page source

7.2.3.4.6. statsmodels.genmod.families.links.NegativeBinomial¶

class statsmodels.genmod.families.links.NegativeBinomial(alpha=1.0)[source]¶

The negative binomial link function

Parameters:

alpha : float, optional

Alpha is the ancillary parameter of the Negative Binomial link function. It is assumed to be nonstochastic. The default value is 1. Permissible values are usually assumed to be in (.01, 2).

__init__(alpha=1.0)[source]¶

Methods

__init__([alpha])
deriv(p) Derivative of the negative binomial transform
inverse(z) Inverse of the negative binomial transform
inverse_deriv(z) Derivative of the inverse of the negative binomial transform
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