# Questions tagged [generalized-linear-model]

A generalization of linear regression allowing for nonlinear relationships via a "link function" and for the variance of the response to depend on the predicted value. (Not to be confused with "general linear model" which extends the ordinary linear model to general covariance structure and multivariate response.)

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### "Percent change" interpretation when we $\log$ the expected value instead of taking the expected value of the $\log?$

When we take the log of the $y$ variable of a regression and then fit the OLS estimator via $(X^TX)^{-1}X^T\log(y)$, we can interpret the regression in terms of percent change in $y$. However, this ...
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### Comparing $R^2$ between Gaussian GLM with identity link and with $\log$ link

It is known that $R^2$ should not be compared between two regressions where one uses features $X_1,\dots ,X_n$ to predict $Y$ and the other uses those same features to predict $\log(Y)$. However, this ...
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### Difference between odds and odds ratio? Interpreting logistic regression coefficients [duplicate]

I was wondering what the difference is between odds and odds ratio in logistic regression. I understand that formally, odds is the probability of success over the probability of failure, however, I ...
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### statsmodels GAM: how to efficiently fit multiple models with identical exog but different endog variables [closed]

I want to fit multiple (several hundred or thousand) generalized additive models using the statsmodels package. I have different response variables $Y_1,...,Y_n$, each of which i want to model with ...
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### Need some advice in selection of GAM model - choosing family, etc

I am not a statistician (clearly) and am trying to wrangle environmental data. My data looks like (note data is on time scale - 1 = Day 1, 650 = Day 30: I am developing a GAM model which predicts the ...
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### Zeros in Dependent Variable : Bad- Zeros in Independent Variables: Not Bad?

I am an MBA Student taking courses in statistics. We have been learning about regression models for count data. Recently, our professor has been talking about situations in which there are a lot of ...
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### How to model insurance count data with a large number of zeros and no number of claims in a period greater than 1

I have a large dataset for insurance claims and I am trying to model both the number of claims and the severity of claims based on a number of explanatory variables using a General Linear model. As is ...
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### Why null deviance is different from my manual calculations?

Let's consider this very simple example with Poisson regression: ...
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### Does a Heteroskedasticity and Autocorrelation Consistent Estimator for generalized linear (mixed/non-mixed) models exist?

Does a Heteroskedasticity and Autocorrelation Consistent Estimator for generalized linear models exist? That would make GEEs outdated unless no-free lunch theorem suggests otherwise. I am only aware ...
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