Skip to main content
clarified
Source Link
Stephan Kolassa
  • 130.7k
  • 22
  • 264
  • 497

What you are trying to do (if I understand you correctly), is to model the probability of the stimulus being seen by a Weibull distribution... but with the Weibull parameters depending on a covariate, i.e., itsthe size of the stimulus. So you are really doing a so-called "Weibull regression". The weibreg() function in the eha package looks like it should do what you want.

What you are trying to do (if I understand you correctly), is to model the probability of the stimulus being seen by a Weibull distribution... but with the Weibull parameters depending on a covariate, i.e., its size. So you are really doing a so-called "Weibull regression". The weibreg() function in the eha package looks like it should do what you want.

What you are trying to do (if I understand you correctly), is to model the probability of the stimulus being seen by a Weibull distribution... but with the Weibull parameters depending on a covariate, i.e., the size of the stimulus. So you are really doing a so-called "Weibull regression". The weibreg() function in the eha package looks like it should do what you want.

Source Link
Stephan Kolassa
  • 130.7k
  • 22
  • 264
  • 497

What you are trying to do (if I understand you correctly), is to model the probability of the stimulus being seen by a Weibull distribution... but with the Weibull parameters depending on a covariate, i.e., its size. So you are really doing a so-called "Weibull regression". The weibreg() function in the eha package looks like it should do what you want.