The correct answer is A. 2.
A generalized linear model (GLM) is a statistical model that links a response variable that has a probability distribution from a specified family to one or more explanatory variables using a linear predictor. In other words, a GLM is a linear model that is used to model a response variable that is non-normally distributed.
A GLM has two main components:
- A linear predictor, which is a linear combination of the explanatory variables.
- A link function, which maps the linear predictor to the response variable.
The link function is chosen so that the response variable has a specified distribution. For example, if the response variable is binomial, then the logit link function is often used.
GLMs are a powerful tool for statistical modeling. They can be used to model a wide variety of response variables, including binary data, count data, and continuous data.
Here is a brief explanation of each option:
- Option A: 2. This is the correct answer. A GLM has two main components: a linear predictor and a link function.
- Option B: 4. This is incorrect. A GLM has two main components, not four.
- Option C: 6. This is incorrect. A GLM has two main components, not six.
- Option D: None of the mentioned. This is incorrect. The correct answer is A. 2.