query: How do I model count data (Poisson regression) that has a seasonal pattern?
positive_passages.docid: 150905
positive_passages.text: Is this an appropriate method to test for seasonal effects in suicide count data?
negative_passages.docid: 50752
negative_passages.text: Linear Regression and group by in R
negative_passages.docid: 26988
negative_passages.text: Interpreting coefficients for Poisson regression
negative_passages.docid: 120542
negative_passages.text: Should the predictor variables be normally distributed for Poisson glm?
negative_passages.docid: 32473
negative_passages.text: which predictive model should I use if column is having string values?
negative_passages.docid: 147893
negative_passages.text: Specifying a difference in differences model with multiple time periods
negative_passages.docid: 96627
negative_passages.text: stl() gives seasonal component, but ets() and auto.arima() choose nonseasonal models
negative_passages.docid: 111580
negative_passages.text: Elegant way to get the count of months between two dates?
negative_passages.docid: 105828
negative_passages.text: Diagnostics and residual analysis for Poisson regression
negative_passages.docid: 84210
negative_passages.text: Overdispersion and Underdispersion in Negative Binomial/Poisson Regression
negative_passages.docid: 2219
negative_passages.text: How do you deal with "nested" variables in a regression model?
negative_passages.docid: 72060
negative_passages.text: Frequency counts in R
negative_passages.docid: 75331
negative_passages.text: test of seasonality
negative_passages.docid: 39804
negative_passages.text: What method can be used to detect seasonality in data?
negative_passages.docid: 140907
negative_passages.text: Fit mixture of distributions to your time-series data in R
negative_passages.docid: 9006
negative_passages.text: Normal approximation to the Poisson distribution
negative_passages.docid: 57834
negative_passages.text: In a Poisson model, what is the difference between using time as a covariate or an offset?