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 ...

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Constraint GLM coefficients

I am using a generalized linear model in R with categorical independent variables. The model is calibrated and validated, but the results are not of good practical use, because the differences in the ...
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6 views

Loss History of Linear Regression in MLlib [on hold]

I am trying to use Linear Regression with SGD but I can't find a way get the stochastic loss for every iteration. The optimize function of the optimizer in GeneralizedLinearModel only returns weights ...
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19 views

Zero inflated GLM and singularities

So I am using a zero-inflated model to (1) model the presence/absence of an animal over certain habitat characteristics using a binomial distribution (2) model the count data over the same ...
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5 views

Zero trick in JAGS for GLMM

I'm trying to do zero trick but i got stuck. I tried the following model: model dGC.model <- function(){ C <- 10000 for(i in 1:(2*m)){ zeros[i] ~ dpois(zeros.mean[i]) zeros.mean[i] <...
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9 views

Compare models with different number of observations (data with strong gender bias )

I am analyzing gene expression data (RNASeq) from patients with recessive X-linked mendelian disorder. What it means is that all affected individuals are males, but controls are both males and females....
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9 views

Pairwise comparisons between GLMs

Apologize for the novice question up front. I'm curious if there's a way to compare glms in R. I've seen some posts on ANOVA, however my independent variable is not categorical, so I don't think it ...
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8 views

Moderation in Generalized Linear Model

I have conducted an experiment with a control group and two experimental groups (each with a different N). The respondents in the three groups were all exposed to same donation situation. Each of the ...
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1answer
18 views

fit GLM for weibull family

I am trying to fit generalized linear model for weibull family, but when I try it in R, it gives an error. I know that weibull does not fit in exponential family, but I have read some research ...
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1answer
15 views

GLM (conditional/unconditional) distribution

Based on my readings about GLM, I am pretty sure that when we say the distribution of the response variable $y$ is a member of exponential family of distribution, what we really mean is that ...
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1answer
21 views

Which glm family to use for ordinal DV?

I'm trying to test whether duration of time spent on the Internet (ratio scale) can predict behavioural problems (ordinal, with scores ranging from 0-10). I just wanted to double check that an ordinal ...
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4 views

Can I analyze planned missing (MNAR) data in unbalanced design using SAS PROC MIXED (Generalized LM)?

In my experiment, there are 3 levels of Treatment (A (control), B, and C). All participants (N=109) underwent two of these treatments, the order of which was determined by random assignment to 1 of 4 "...
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2answers
36 views

Logistic regression with only categorical predictors

So I started off with a model which included both continuous and categorical predictor variables. But now I wanted to drop the only continuous variable (distance to shore), because to my opinion it ...
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1answer
26 views

How can standard logistic regression model fractional response variable while denominator is available?

I have X and Y variables, as well as a cluster variable (State). X and State are derived from Database A, while Y and State are derived from Database B. X is a sentiment score ranging between -1 and ...
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How to model GEE (generalized estimating equation) in data coming from two datasets?

I would like to model X (sentiment score, continuous between -1 and 1) and Y (smoking status, either 0 or 1). Individuals can be clustered by the "State" variable. It would be the most ideal if I ...
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13 views

Glmnet standardize not consistent with prior standardization

I am running glmnet with standardize=TRUE. Now I try to pre-standardize my data, and un-standardize after the regression. But the results are inconsistent: ...
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1answer
34 views

Link functions for Binomial Regression

So I have a dataset of presence (1) and absence (0) data, but it mainly consists of 0's (~80% of the 5200 observations). Now while constructing my binomial logistic model I am reading (Zuurt et al. ...
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1answer
18 views

drop1 LRT is zero in R

So for my current binomial model I am dropping some components and I found out that for one variable the results look a bit different. For 'hurseason' (class factor with two levels Y/N), the LRT is ...
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17 views

How the distribution affects the calculation of the coefficient in a GLM?

I was wondering how the distribution specified in a GLM changes the coefficients. If I have understood the process, when you fit a GLM, let's say $g(E[Y|X])=X\beta$, most of the software and R ...
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1answer
30 views

Interpreting dispersion parameters of poisson GLMM with count data

I am working with count data and trying to understand if my model fit is acceptable for this poisson Generalized Linear Mixed Model: Richness.glmer<-glmer(Richness ~ Unit.type + plot.type + (1|NFI....
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What to do when the predicted versus the residuals are clumped in a negative binomial model

I'm working on trying to find out which variables are most important in explaining the amount of research that one country does in another country. The response (the number of studies) is highly ...
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7 views

what should be validation parameter for Logistic Regression(LR) in online learning plus rare event scenario?

We have been following below paper to predict CTR( Click probability) of different ad items. This will be used to serve different ads based on probability values. http://olivier.chapelle.cc/pub/...
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RFE (Recursive Feature Elimination) for Poisson Regression with offset [migrated]

It's my first post so I hope I don't make any editing mistakes. Here's my issue : I'm working on count data and am implementing a Poisson Regression with an exposure factor (that needs to go in the "...
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Linear model for testing a ratio of ratios

Our experimental design is as follows: For each of two genotypes (wt and ko), we perform two different gene expression assays (Assay1 and Assay2), and do 4 replicates of each assay. We are interested ...
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19 views

Model design and nonconvergence problem with GLMM, incomplete block design in R

I have a two-part question that includes issues with generalized linear mixed models and failure to converge. First, a little bit about my experimental design. I have data where I am trying to test ...
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39 views

Book about generalized linear models [duplicate]

Does anyone know a good book about generalized linear models. I am a practitioner and need to master the concepts of generalized linear model, but also my experience tells me that knowing about the ...
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45 views

EM parameter estimation for conditional Gaussian model [duplicate]

Let $$X_1\sim N(\mu_{X_1},\sigma_{X_2}^2)$$ $$X_2\sim N(\mu_{X_2}, \sigma_{X_2}^2)$$ where $\mu_{X_2}=c+aX_1$. Also, I have data $D$ (with missing values on $X_1,X_2$). How can I update/estimate the ...
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What is the use of the quantile information on the deviance residuals?

For example, in R we can fit the following glm: model <- glm(formula = am ~ mpg + qsec, data=mtcars, family=binomial) The ...
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1answer
46 views

Can a generalized linear model use shifted exponential as residual distribution?

I am facing a modeling problem: $t_{ij} = D_i + T_j + \epsilon_{ij}, i=0...641, j\in\mathbb{N}$ where $\epsilon_{ij}$ follows exponential distribution, $\epsilon_{ij} \sim \lambda e^{-\lambda t}, \...
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Data distribution in GLM [closed]

I want to do glm analysis for my data in r studio, my data are soil data (PH soil, percentage of clay and silt and loam, nitrogen soil), I have 5 plantation and 3 soil depth, plantation and soil depth ...
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95 views

Using lm for 2-sample proportion test

I have been using linear models to perform 2-sample proportion tests for a while, but have realized that might not be completely correct. It appears that using a generalized linear model with a ...
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19 views

Determining the Repeatability and Reproducibility (Gage R&R) in Minitab within a General Linear Model

I am doing some rather complex data analysis and I was wondering if it was possible to determine the reproducibility and repeatability of a measurement system within a GLM in Minitab. In this data, ...
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7 views

significance between comparisions

I hope this is the right forum for this kind of question (otherwise please point me to the right one). We are working on a RNA-Seq data set (10 biological replica for three conditions). We have ...
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8 views

Comparing importance of predictors in different datasets in GLM

I want to compare the importance or 'predictive power' of the same feature/covariate in 2 different datasets. Specifically let $[\bf{y}_1,\bf{V}_1]$ be my output & design matrix of dataset 1 & ...
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1answer
23 views

Goodness of fit: Generalized Linear Models with missing values in R

I am trying to compare two models and check which is the best fit of our data. The R script is below: ...
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1answer
45 views

Best way to analyse percentage data

I have percentage data and would like to see if these different variables have an affect on certain factors; i.e., I have different habitats of an area e.g., improved grassland: 40%, arable: 15%, ...
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8 views

Suggested methods when logistic regression outperforms with boosted outliers

I am using logistic regression to predict binary outcomes with 5 features. When putting 20x weight on the 0.001% outliers the peformance gets a lot better. It seems that some really high/low values ...
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1answer
64 views

How do distribution functions (e.g. Gaussian, Bernoulli, Poisson, etc.) relate to deep learning?

I know that neural nets use activation functions, but where do distribution functions play into deep neural networks? For example, the h2o.deeplearning() function ...
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1answer
40 views

MCMC for Probit/Logit model with some 1's flipped to 0's

I would like help constructing a sampler for the following model, which is the latent variable interpretation of either logistic or probit glm (doesn't matter which one to me), with a small twist: ...
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1answer
29 views

Can I report simple main effects without an interaction effect?

I have a quick question about reporting simple main effects. I am running a two-way mixed ANOVA and the interaction effect was not significant. I understand that if you have no significant interaction ...
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27 views

Linear or non-linear model for social interaction with R

The question here is whether the cooperation of people with equal or similar abilities leads to better results than the cooperation of people with different abilities. The setting is a group of ...
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24 views

collinearity in conditional logistic regression: glm vs coxph

I am fitting some conditional logistic regression models to wildlife radio telemetry data using a 1:1 paired design, specifically where habitat features at a single telemetry point are compared to ...
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6 views

Residuals for zero bounded data

So, I'm running into an interesting problem with my residual plot. For reference, I'm trying to model a response variable "exploration" for a social network. Exploration is the number of people you ...
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58 views

Using PCA to model highly correlated variables

Specifically, Andrew Ng states that PCA should be used to speed up algorithms or to visualize data. He also states that using PCA as a way to prevent overfitting is an incorrect application of PCA. ...
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1answer
39 views

How to improve a regression model without making new measurements? [closed]

Assuming I can't make more measurements, how can I improve a linear model regression? I have the following data: ...
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20 views

How to analyse this hierarchical-like data better?

I have a dataset whose structure is as below. Here f1, f2, f3 etc are a set of features. There are differennt models to predict each Vi from all fjs. There are different models to predict each Wi ...
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31 views

Negative main effect but positive interaction - GLM in R [duplicate]

I am comparing the density of bird species within towns/cities and the countryside and am interested to see how different habitats affect this. So, I want to see if different habitats (improved ...
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0answers
3 views

Given these residual and pair plots how should I model the data

I have used the pairs() function in R and here are the results: I used the lm function and the residual plots were obviously ...
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19 views

How to add a random effects term to a generalized poisson regression model?

I want to add random effects terms to a generalized poisson regression model. I know this will involve approximation of the loglikelihood (laplace or Gaussian quadratures). Please, i need some more ...
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Can you use the Poisson GLM if there is an upper limit?

I'm analyzing social network data where roughly 10 groups of 100 people are split into different sized teams. (For example, there are 10 schools, but some of the schools have 5 "classrooms" while ...
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1answer
45 views

Negative binomial regression in R allowing for correlation between dispersion & regression coefficients

In negative binomial regression, the MLE of the dispersion parameter is asymptotically uncorrelated with the MLEs of the regression coefficients (http://pointer.esalq.usp.br/departamentos/lce/arquivos/...