# Tagged Questions

Quasi-likelihood is a function similar to but not likelihood, and it was introduced by Wedderburn (1974) and mainly used in generalized linear models.

50 views

### How to measure goodness of fit for a poisson regression model?

I am working on a poisson regression model in sas. But I am not able to determine how good the fit is. I have used PROC GENMOD, PROC NLMIXED, PROC GLIMMIX and now I want to compare the results. How ...
21 views

### Composite-likelihood ratio test

I am interested in a number of articles (such as Kim and Stephan 2002 and follow-up articles) that use composite likelihood ratio tests to infer selection pressure on linked (phased) genetic data. I ...
26 views

### Gaussian QMLE in estimating GARCH model

I am having some troubles understanding the estimation of a CCC-GARCH model (where the univariate GARCH models are GJR-GARCH(1,1)) by the means of Gaussian QMLE with the likelihood function of ...
11 views

### Quasi-likelihood increases or decreases when mu_i and y_i are closer?

I have a question about quasi-likelihood. I think the following formula says something opposite to what likelihood means. Could someone clarify what I'm misunderstanding. I'm looking at the formula ...
18 views

### How to decide between quasi-poisson and negative binomial?

I tried quasi-poisson and negative binomial glms on my counted data in R. The estimates are pretty much the same but p-value are different. Quasi-poisson gives insignificant result. NB give ...
28 views

### Central limit theorem for maximum likelihood estimators when modelling assumptions are violated

Lehman's Element's of Statistical Learning Theory gives in Theorem 7.5.2 a central limit theorem for multiparamter maximum likelihood estimators. (Many other sources provide similar theorems.) The ...
20 views

### Frequency Data, Model Choice (Poisson with Offset, Fractional Regression)

I have text data and am interested in estimating the effect of some covariate on word frequency. All the frequencies are very small. The unit of observation is a single document. I'm trying to think ...
83 views

### Idea and intuition behind quasi maximum likelihood estimation (QMLE)

Question(s): What is the idea and intuition behind quasi maximum likelihood estimation (QMLE)? What makes the estimator work when the actual error distribution does not match the assumed error ...
84 views

### Diagnostics for quasipoisson glm for continuous data

I'm a little confused about how to use the quasipoisson family in the glm function. It was recommended by someone that I use it for my analysis, even though the data are continuous - and as such, I ...
86 views

### Scaling vs Offsetting in Quasi-Poisson GLM

I recently modeled insurance claim frequency assuming a Quasi-Poisson distribution in R. My frequency dependent variable was calculated, in advance of modeling, as the number of claims per underlying ...
10 views

### Number of parameters for a GEE

How can I determine the number of parameters I have for each of 2 Generalized Estimating Equations, as well as the log-quasi-likelihood for each equation, using R? I am using the geepack library, R ...
91 views

### How can compare a Poisson model against a Quasipoisson model in GAM?

I have count data of species and I would like to fit a GAM model in mgcv with poisson distribution. The poisson model has overdispersion so I have read that is better to fit a quasipoisson ...
28 views

### Why does GEE produce the same parameter estimates as OLS?

The quasi-likelihood function optimized under GEE is: $S_k(\beta)=\sum_{i=1}^{K}\frac{\partial\mu_i}{\partial\beta_k}\nu_i^{-1}(y_i-\mu_i)=0,$ where $\mu_i=h(\textbf{x}_i,\beta)$ is the conditional ...
141 views

### GLM Model checking Plots - Quasi Poisson - Poisson

I wonder whether accounting for overdispersion in a GLM (Quasi - Poisson instead of Poisson family) has an effect on the model checking plots (plot of residuals against fitted values, a scale–location ...
57 views

### Generalized linear model using quasi-likelihood

I am going to fit a model using quasi likelihood, (because the dispersion parameter > 1, y is a binary data). But when I ...
640 views

### compare quasi poisson models

I have two models: ...
116 views

### What properties of a likelihood function are required for quasi-likelihood estimation?

Quasi-likelihood seems like a great way to use Iteratively Weighted Least Squares to fit linear linear models with a very general class of likelihoods. But what is that class? Obviously the ...
323 views

### GLM analogue of weighted least squares

The short version: I can fit a model using Weighted Least Squares, given a diagonal matrix of weights $W$, by solving $(X^TWX)\hat{\beta}=X^TWy$ for $\hat{\beta}$. Is there a GLM analogue? if so, ...
1k views

### How to handle underdispersion in GLMM (binomial outcome variable)

I'm working on the following model in R: ...
97 views

293 views

### GLM quasi family with log transformation?

I am working on my thesis analysis, and I have some error data that's right-skewed. I log-transformed it and ran glm on it (gaussian, identity in R) weighted by sample size, and my data is still over-...