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votes
1answer
147 views

Can GLM( generalized linear method) handle the collinearity between the predictor variables in a regression-analysis?

I'm a beginner in Machine learning and I've studied that collinearity among the predictor variables of a model is a huge problem since it can lead to unpredictable model behaviour and a large error. ...
0
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0answers
27 views

Including spatial spillover for categorical data in R

I did a regression analysis with categorical data with a glm model approach, which worked fine. I have longitude and latitude coordinates for each observation and I ...
0
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0answers
12 views

Plot ROC curves in R conditional on a fixed-effect

I have a model of the form mylogit <- glm(y~x+as.factor(year)+as.factor(city), data=d, family="binomial") How can I plot the ROC curve (or get the ROC score) ...
0
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0answers
12 views

How to model a decimal response between 0 to 1 with a GLM in R

I am trying to model a response variable which is a proportion (so a response between 0 and 1, see picture for distribution). Ideally I would like to model it without using the actual counts, so as a ...
0
votes
0answers
35 views

Generalised Estimating Equation (GEE) vs. Recurrent Neural Network (RNN)

Has anyone looked into or know what is the difference between a GEE model and an RNN model in terms of what these two models are doing? Apart from the differences in structure of these two models ...
1
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0answers
41 views

Problem in performing LOOCV

I am trying to run LOOCV on my regression model. I tried to run it in r and encountered the following warning message: ...
1
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1answer
26 views

Fitting glm without explicit declaration of each covariate

When I fit a linear model with many predictor variables, I can avoid writing all of them by using . as follows: ...
0
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0answers
16 views

goodness of fit metrics to compare neural network and GLM model for count data

I´m wodering if some of you have compared goodness of fit of a NN and a GLM model on count data and which metrics you used? In addition, the data I´m dealing with has a point mass at zero. Are there ...
1
vote
0answers
47 views

Select the right distribution

I have a dataset like: ...
4
votes
2answers
89 views

How to interpret two continous variables output using GAM?

I really need help with GAM. I have to find out whether association is linear or non-linear by using GAM. The predictor variable is temperature at lag0 and the output is cardiovascular admissions (...
1
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0answers
235 views

LASSO Regression using Panel Data

I have panel data for 3 countries, ranging over 3 years. The dataset is called CarProduction ...
2
votes
1answer
214 views

Select behavior dependant with other factors and its formalization

I'm studying occurence of Behavior11, Behavior12,Behavior2,...
1
vote
1answer
74 views

Combining outputs of ridge regression models?

I am facing an issue where I have 7 sets of different variables/columns/predictors. I am trying to predict same target variable and I want to observe the importance/effect of all the sets according ...
1
vote
1answer
285 views

r glm - Error in names(coef) <- xnames only for 2 columns in data

I am getting the below error when i run the R code for glm(): ...
3
votes
1answer
58 views

Alternative to VGAM for Zero Truncated Negativ Binomial GLM in R

Is there an alternative to the vgam Package to do a zero truncated negativ Binomial GLM in R?
1
vote
1answer
67 views

Changing reference class in imbalanced data drastically affects the error rate

Working on a binary classification problem that tries to predict customer churn, the data set is imbalanced with 2000 observations of non-churn cases vs 600 observations of churn cases. On using GLM ...
2
votes
2answers
854 views

How do I compare coefficients from my glm when I have more than one factor variable in my formula?

I am trying to model a binary outcome in R that has many independent variables. 5 of the Ivs are factors with more than two levels. When I try to remove the intercept it only does it for one of the ...
2
votes
1answer
151 views

Searching interactions with RandomForest and/or GBM

I'm trying to explain a count variable and a continious variable > 0 with GLM, using R. In order to improve the quality of the regression, I want to add some interactions that can be useful for the ...
-1
votes
1answer
329 views

R how to find the top key parameters contribute to the response var change in two tables?

For example, if I create two tables, both contain multiple kinds of data: numeric (integer), numeric (continuous), and factor (character) like below: ...
2
votes
0answers
37 views

Outputting risk groups for a logistic regression model

I have a problem with outputting the terms for a logistic regression model in R. For a given list of independent values, say list l of terms {w,y,z} to determine dependent variable {x}, I want to ...
2
votes
0answers
93 views

How can I use idh and random when I use hupossion in mcmcglmm?

Here is my problem: I need to use hupossion in MCMCglmm package. Here is my prior: ...
2
votes
1answer
9k views

Extracting model equation and other data from 'glm' function in R

I've made a logistic regression to combine two independent variables in R, using pROC package and I obtain this: ...
3
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2answers
128 views

Extrapolating GLM coefficients for year a product was sold into future years?

I've fit a GLM (Poisson) to a data set where one of the variables is categorical for the year a customer bought a product from my company, ranging from 1999 to 2012. There's a linear trend of the ...
11
votes
4answers
11k views

Is GLM a statistical or machine learning model?

I thought that generalized linear model (GLM) would be considered a statistical model, but a friend told me that some papers classify it as a machine learning technique. Which one is true (or more ...