Linked Questions

3 votes
0 answers
1k views

Do generalized linear models allow non-normal response variables, non-normal errors, or both? [duplicate]

There are a lot of Generalized Linear Model questions on here, but I couldn't find one that explicitly addressed this point. The Wikipedia page starts out by saying: [T]he generalized linear model ...
user1205901 - Слава Україні's user avatar
0 votes
0 answers
482 views

why in logistic regression the error terms (residuals) do not need to be normally distributed? [duplicate]

In linear regression, one of its assumption is the residual should be normally distributed. Why does it in logistic regression, the assumption says that residuals do not need to be normally ...
Samuel Vera's user avatar
0 votes
0 answers
69 views

Logistic Regression Vs Simple Regression [duplicate]

I am new to this area of regression analysis why do we select ${e^{\beta x } }/{[1+e^{ \beta x}]}$ as $p\{Y=1|X\}$ or how to get $E(y |x )$ in the case where $y$ is dichotomous.
Milan Amrut Joshi's user avatar
0 votes
0 answers
65 views

Assumption of error of logistic regression [duplicate]

I know there are debates about whether the error exists and its distribution in the case of logistic regression. Suppose we assume that the error term follows the logistic distribution. Are we ...
Yuan's user avatar
  • 503
32 votes
2 answers
6k views

Why do we model noise in linear regression but not logistic regression?

The canonical probabilistic interpretation of linear regression is that $y$ is equal to $\theta^Tx$, plus a Gaussian noise random variable $\epsilon$. However, in standard logistic regression, we don'...
kennysong's user avatar
  • 1,061
23 votes
2 answers
13k views

Is there i.i.d. assumption on logistic regression?

Is there i.i.d. assumption on the response variable of logistic regression? For example, suppose we have $1000$ data points. It seems the response $Y_i$ is coming from a Bernoulli distribution with $...
Haitao Du's user avatar
  • 36.9k
2 votes
1 answer
13k views

What to do with GLM (Gamma) when residuals are not normally distributed?

Until now I have only done very basic/simple simple stats, but now I got stuck in all the literature/tips/forums ... It's about the following problem: I have the following data: ...
Lotw's user avatar
  • 123
8 votes
2 answers
3k views

How is Logistic Regression related to Logistic Distribution?

We all know that logistic regression is used to calculate probabilities through the logistic function. For a dependent categorical random variable $y$ and a set of $n$ predictors $\textbf{X} = [X_1 \...
Eduardo Vieira's user avatar
3 votes
1 answer
7k views

How to compute the residual standard deviation from `glmer()` function in R?

I want to extract standard deviation of residual from glmer() function in R . So I wrote : ...
user81411's user avatar
  • 771
4 votes
1 answer
4k views

How can logistic regression have a factorial predictor and no intercept?

I tried a regression in the form ${\rm logit}(Y) = {\rm coefficient}\times X + 0 + e$, where $Y$ is a binomial variable and $X$ is a factor variable with $n$ levels. I noticed that removing the ...
Bakaburg's user avatar
  • 2,917
1 vote
1 answer
3k views

How to write a logit and probit regression equation?

I have the following linear equation: Dummy dependent variable = dummy main independent variable + control variable 1, absolute value of changes (also between 0 and 1) + control variable 2, sigma (...
David's user avatar
  • 11
2 votes
1 answer
4k views

binary logit regression - which test apply for detecting heteroskedasticity?

After reading a lot of different papers and a lot of different posts on the internet I still don't have a clue how to test on heteroskedasticity with my logistic regression (binary). The White test ...
jenny's user avatar
  • 21
9 votes
1 answer
291 views

Why does R refer to the distribution family as an "error distribution" in the context of generalized linear models?

I was wondering why R refers to the distribution family as an "error distribution" in the context of generalized linear models? Normally distributed errors(residuals) of a fitted model are a key ...
Ryan's user avatar
  • 351
3 votes
1 answer
767 views

What is the distribution of the error term in the Poisson Regression model? [duplicate]

Given a Poisson regression model as $y = E(y\mid x) + ε$ where $λ = E(y\mid x) = \exp(x'β)$ with $y$ from the Poisson distribution ($\operatorname{Poisson}(λ)$) I am trying to understand the ...
Dick's user avatar
  • 95
1 vote
0 answers
2k views

What's the difference between error distribution and residual distribution in generalized linear models? [duplicate]

I have met with generalized linear model, but I'm confused with the errors and residuals? Can anyone help me out? I have got three questions. (1)what's the difference between error and residual? (2)...
Hongtao Xiao's user avatar

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