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Results tagged with generalized-linear-model
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user 129321
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.)
2
votes
Poisson family GLM with 1 categorical independent variable error missing value where TRUE/FA...
Yes, you definitely need a different test.
First, the reason for the error message is that you are inputing a factor to the glm function, which was expecting to get numerical counts.
To illustrate thi …
- 13.5k
3
votes
Accepted
GLM - overfitting
The difficulty in answering your question is that the scenario you describe is essentially not possible. Except in special degenerate cases, it is not possible to use just 10 linear model parameters t …
- 13.5k
2
votes
Poisson generalized linear model (glm) sample size
For Poisson glms, statistical power depends just as much on the size of the counts as on the number of count observations. Larger counts provide more precision, in fact the coefficient of variation of …
- 13.5k
6
votes
What's a good textbook with lots of real life examples on GLM and statistical inference?
The CRAN package GLMsData contains nearly 100 real life datasets that are analyzed in the textbook on GLMs by Peter Dunn and myself. Our book includes complete runnable code and output for each datase …
1
vote
Comparing weights between significant predictors in GLM with binomial outcome
In my opinion, the $\beta'_j$ measure you propose doesn't have a useful role in understanding logistic regression and you would be better of using traditional generalized linear model summaries.
Here …
- 13.5k
4
votes
Accepted
quasi likelihood for ungrouped binary data
Suppose $Y$ is a binary random variable that takes value 1 with probability $p$ and 0 with probability $1-p$.
Then
$$E(Y)=0(1-p)+1p=p$$
and
$$\mbox{var}(Y)=E(Y^2)-E(Y)^2=0^2(1-p)+1^2p-p^2=p(1-p).$$
Th …
- 13.5k
15
votes
Accepted
Given a GLM using Tweedie, how do I find the coefficients?
Are you familiar with generalized linear models in R? If so, you can fit Tweedie glms just like any other glms.
The glm family definition necessary to make this happen is provided by the statmod R pac …
- 13.5k
4
votes
Generalised linear models (for dummies)
This is a self-citation, but I think it is a good match to what you're after:
Dunn, P. K., and Smyth, G. K, (2018). Generalized linear models with examples in R. Springer, New York, NY. (Published 11 …
- 13.5k
7
votes
For model-averaging a GLM, do we average the predictions on the link or response scale?
The optimal way of combining estimators or predictors depends on the loss function that you are trying to minimize (or the utility function you are trying to maximize).
Generally speaking, if the loss …
- 13.5k
6
votes
Interpreting GLM residual plot
You could consider using randomized quantile residuals, which use randomization to average out the discrete patterns that appear in residuals from count response data. Randomized quantile residuals ar …
- 13.5k
2
votes
Accepted
quasi-likelihood estimates of beta
The question does not ask you to find the beta estimates or to conduct a test. The only thing you need is the asymptotic covariance matrix, which is given earlier in the same Chapter in the book. You …
- 13.5k
2
votes
Accepted
Quasi-Poisson GLM, can't make sense of the p-values for Goodness-of-fit
Here is the analysis of deviance table from R for the Poisson regression:
> anova(mod, test="Chisq")
Analysis of Deviance Table
Model: poisson, link: log
Response: count
Terms added sequentially ( …
- 13.5k
6
votes
Does the dependent variable in a GLM have to be transformed before running the model or does...
One of the fundamental motivations for generalized linear models (GLMs) is that they model the data as it is instead of transforming it. So the answer to your question is that there is no transformati …
- 13.5k
4
votes
Accepted
In a normal GLM is the dispersion parameter equal to the marginal variance?
Yes, in a normal generalized linear model (GLM) the dispersion parameter and the variance are the same thing.
If you are fitting a normal GLM with identity link (which is the default) then you may as …
- 13.5k
4
votes
What GLM family and link function to use with similarity index as response variable?
There is no generalized linear model (GLM) for continuous proportion data on (0,1), but there are two approximate possibilities.
The first possibility would be a quasi-GLM family with a beta distribu …
- 13.5k