I performed my work in R. I used the library dplyr for sampling, the library PROC for testing the fit of a logistic regression, and the library aod to test the significance of logistic regression. I ...

In practice, you can implement both linear and logistic regression using statistical software packages. For example, in R, you can use the lm() function for linear regression and glm() function ...

#Analyzing Age and Gender Distribution in Diabetes Dataset # Step 1: Create Age Groups, allowing for missing values # Note the link = logit is not mandatory for logistic regression in R, but it is the ...

Logistic regression is a type of regression analysis ... statistical data analysis and programming in R. I would be careful to apply it to estimation of survival, as it misses some important ...

The LOGISTIC procedure in SAS/STAT software fits linear logistic regression models for binary or ordinal response data by the method of maximum likelihood. Subsets of explanatory variables can be ...

Abstract: We study a staffing optimization problem in multi-skill call centers. The objective is to minimize the total cost of agents under some quality of service (QoS) constraints. The key challenge ...