Contents
- 1 Can I use linear regression for discrete data?
- 2 Which type of regression analysis is used when the dependent variable is count based?
- 3 Is there a module for discrete dependent variable regression?
- 4 How are all discrete regression models the same?
- 5 How are regression problems and classification problems related?
Can I use linear regression for discrete data?
If you have a discrete variable, you can decide whether to treat it as a continuous or categorical predictor. A discrete variable can be measured and ordered but it has a countable number of values. If you have one continuous predictor, you can use Simple Regression.
Which type of regression analysis is used when the dependent variable is count based?
Nonlinear regression models are appropriate for count data because they use probability distributions for the dispersion of the dependent variable scores around the expected value for dependent variables which take on only nonnegative integer values (Kutner et al., 2005).
What type of regression is used when the dependent variable is dichotomous?
binomial logistic regression
A binomial logistic regression is used to predict a dichotomous dependent variable based on one or more continuous or nominal independent variables. It is the most common type of logistic regression and is often simply referred to as logistic regression.
Is there a module for discrete dependent variable regression?
Regression with Discrete Dependent Variable Regression models for limited and qualitative dependent variables. The module currently allows the estimation of models with binary (Logit, Probit), nominal (MNLogit), or count (Poisson, NegativeBinomial) data.
How are all discrete regression models the same?
Currently all models are estimated by Maximum Likelihood and assume independently and identically distributed errors. All discrete regression models define the same methods and follow the same structure, which is similar to the regression results but with some methods specific to discrete models.
What are the different types of regression analysis?
Guest blog by Jim Frost. Regression analysis mathematically describes the relationship between a set of independent variables and a dependent variable. There are numerous types of regression models that you can use.
There are regression problems and classification problems. Basically, given some features (discrete (car model) or continuous (Miles per Gallon)) you want to estimate the price (a continuous variable). Your model will use the independent variables (your features) to estimate the dependent variable.