query: How can Poisson GLM work with non-count data (rate data)?
positive_passages.docid: 148768
positive_passages.text: How is it possible that Poisson GLM accepts non-integer numbers?
negative_passages.docid: 102653
negative_passages.text: percentage count by group using dplyr
negative_passages.docid: 75506
negative_passages.text: MLE for Poisson-binomial distribution
negative_passages.docid: 94847
negative_passages.text: Why is GLM different than an LM with transformed variable
negative_passages.docid: 148924
negative_passages.text: Zero-inflated Poisson regression Vuong test: Raw, AIC- or BIC-corrected results
negative_passages.docid: 7539
negative_passages.text: Deseasonalizing count data
negative_passages.docid: 120542
negative_passages.text: Should the predictor variables be normally distributed for Poisson glm?
negative_passages.docid: 77039
negative_passages.text: Statistical test in R for count data
negative_passages.docid: 150197
negative_passages.text: Generalizing Poisson's binomial distribution to the multinomial case.
negative_passages.docid: 103176
negative_passages.text: Two independent Poisson process question
negative_passages.docid: 5675
negative_passages.text: Difference between offset and exposure in Poisson Regression
negative_passages.docid: 17185
negative_passages.text: What is the meaning of the correlation in glm
negative_passages.docid: 114189
negative_passages.text: How does one show that there is no unbiased estimator of $\lambda^{-1}$ for a Poisson distribution with mean $\lambda$?
negative_passages.docid: 42591
negative_passages.text: Simulate simple non-homogeneous Poisson proces
negative_passages.docid: 148126
negative_passages.text: Binomial response and logit link function in GLM (r)
negative_passages.docid: 29763
negative_passages.text: What regression model is the most appropriate to use with count data?
negative_passages.docid: 47349
negative_passages.text: Poisson solver using Mathematica