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Derivation of the Binary Logistic Algorithm
| Content Provider | Scilit |
|---|---|
| Author | Hilbe, Joseph M. |
| Copyright Year | 2009 |
| Description | It is important to have an overview of how the logistic model is derived from the Bernoulli probability distribution function, which we have already seen is a subset of the general binomial PDF. In this chapter we shall derive the statistical functions required for the logistic regression algorithm from the Bernoulli PDF. In the process we address functions that are important to model convergence and the estimation of appropriate parameter estimates and standard errors. Moreover, various statistics will emerge that are important when assessing the fi t or worth of the model. Book Name: Logistic Regression Models |
| Related Links | https://content.taylorfrancis.com/books/download?dac=C2009-0-08057-1&isbn=9780429149139&doi=10.1201/9781420075779-6&format=pdf |
| Ending Page | 90 |
| Page Count | 10 |
| Starting Page | 81 |
| DOI | 10.1201/9781420075779-6 |
| Language | English |
| Publisher | Informa UK Limited |
| Publisher Date | 2009-05-11 |
| Access Restriction | Open |
| Subject Keyword | Book Name: Logistic Regression Models |
| Content Type | Text |
| Resource Type | Chapter |