Questions tagged [gamlss]

Generalized additive models for location, scale and shape (GAMLSS).

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25
votes
1answer
3k views

What diagnostic plots exists for quantile regression?

Following on my question for OLS, I wonder: what diagnostic plots exists for quantile regression? (and are there R implementation of them?) A quick google search already came up with the worm plot (...
22
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3answers
15k views

Regression modelling with unequal variance

I would like to fit a linear model (lm) where the residuals variance is clearly dependent on the explanatory variable. The way I know to do this is by using glm with the Gamma family to model the ...
12
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2answers
842 views

Parametric modelling of variance of count data

I am looking to model some data, but I am not sure what type of model I can use. I have count data, and I want a model that will give parametric estimates of both the mean and the variance of the ...
11
votes
1answer
4k views

Convert SAS NLMIXED code for zero-inflated gamma regression to R

I'm trying to run a zero-inflated regression for a continuous response variable in R. I'm aware of a gamlss implementation, but I'd really like to try out this algorithm by Dale McLerran that is ...
10
votes
1answer
922 views

Significance of (GAM) regression coefficients when model likelihood is not significantly higher than null

I am running a GAM-based regression using the R package gamlss and assuming a zero-inflated beta distribution of the data. I have only a single explanatory variable in my model, so it's basically: <...
9
votes
2answers
8k views

Simulate linear regression with heteroscedasticity

I am trying to simulate a dataset that matches empirical data that I have, but am unsure how to estimate the errors in the original data. The empirical data includes heteroscedasticity, but I am not ...
9
votes
1answer
873 views

Prediction interval for a future proportion of successes under Binomial setting

Suppose I fit a Binomial regression and obtain the point estimates and variance-covariance matrix of the regression coefficients. That will allow me to get a CI for the expected proportion of ...
8
votes
3answers
4k views

fit GLM for weibull family [closed]

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 ...
8
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3answers
3k views

How to model zero inflated, over dispersed poisson time series?

I am trying to model weekly disease counts in 25 different regions within 1 country over a ten year period as influenced by temperature. The data is zero inflated and over dispersed. I am most ...
6
votes
3answers
2k views

Are Random Forests more powerful than generalized linear models?

I have never used Random Forests, but I have read some about it. Until now I have used GLM/GAMLSS extensively. I would like to know: What are the advantages that RF provides over GLM/GAMLSS? What ...
6
votes
2answers
2k views

Overdispersed poisson or negative binomial regression

I am performing a GLM on count data (insurance claims) and I wish to compare Overdispersed Poisson Regression (ODP) against Negative Binomial regression. would know whether there is a practical ...
6
votes
2answers
396 views

Create Spline from Coefficients and Knots in GAMLSS

In the R package GAMLSS, it is possible to model a random variable $Y$ as a smoothed non-parametric function of some predictor $x$. One option for such a function is the penalised spline using ...
5
votes
1answer
4k views

Zero inflated beta regression using gamlss for vegetation cover data

My goal is to analyse vegetation cover data. The way the data collection works is that you throw a quadrat (0.5m x 0.5m) in a sample plot and estimate the percent cover of the target species. Here is ...
5
votes
2answers
6k views

Modelling zero-inflated proportion data in R using GAMLSS

I am new to the gamlss package and would like to check that I am using the correct family for proportion data (tree species cover after treatment), which is bounded ...
5
votes
1answer
295 views

How can GAMLSS relax the GLM exponential family assumption?

Generalized Additive Models for Location, Scale and Shape "relax the assumption of exponential families" in comparison to GLM's or GAM's. This is a direct quote from the paper by Rigby and ...
5
votes
1answer
106 views

Smoothed Moments as Function of Predictor

Setup Let $x$ describe a continuous predictor variable (e.g. age). Let $Y$ be a random variable (e.g. height) which is some function of $x$. The data consists of $n$ points, each a combination of $x$...
5
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0answers
257 views

How do I account for temporal autocorrelation?

I am trying to fit a beta regression model using GAMLSS. The data: For each $y$, we have an indication of what patient $p$ it is, an indication of what month $m$ the observation took place, and at ...
4
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2answers
127 views

What does it mean to perform regression using a specific distribution?

When we specify the family= argument inside glm() in R, how is the distribution being used ...
4
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3answers
675 views

Zero-truncated Sichel distribution in R

I'm trying to fit the GAMLSS library's Sichel distribution to some zero-truncated data, but the only way to get the function to work is to include the zero-class anyway but give it a frequency of 0, ...
4
votes
3answers
817 views

Is it possible to calculate variable confidence intervals, conditional on $\hat{Y}$ to address heteroscedasticity?

Estimating confidence intervals for non-normally distributed residuals can be accomplished using bootstrapping procedures, sandwich estimators or quantile regression. But is there a way to calculate $...
4
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1answer
2k views

Why is Poisson regression different with glmer and gamlss?

I have a set of count data that seems to fit "Poisson" = not overdispersed, alpha = 0. The problem is, I get different results using gamlss vs ...
4
votes
1answer
741 views

GAMLSS: model with interaction terms failed

I use gamlss method from library(gamlss) on my full models with interaction terms and try to reduce them with stepGAIC. There are 3 things I want to ask. Do I have to specify a link for the model? ...
4
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0answers
2k views

How to fit a regression for log-normal with gamlss

Since my original question was to R-code-specific I'm trying to rewrite it: I want to make a regression where my dependent variable y should follow a log-normal-...
4
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0answers
242 views

Is there a way to add covariates to centile GAM curves in R?

Using the package "mgcv" I fitted a GAM to demonstrate head circumference changes over the lifetime for data stemming from two different countries; ...
3
votes
1answer
323 views

How do gamboostLSS and gamlss packages predict outside range of x?

The mgcv package performs a linear extrapolation when the newdat argument of the predict ...
3
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0answers
55 views

Case of a cubic spline, basis functions

I was studying the basis functions as describes in the Elements of Statistical Learning book on p.143. More precisely, I looked at the basis functions of that particular for cases. While the topleft ...
3
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0answers
873 views

Overall p-value for zero-inflated beta regression mixed model

I am analysing vegetation percentage cover data from grazed and ungrazed plots in R using a zero-inflated beta regression in package gamlss. Here are some example ...
3
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0answers
129 views

Methods for smearing multidimensional data

I have a dataset $X \in \mathbb{R}^{2p}$. Half of the parameters $X_{pre} \in \mathbb{R}^p$ represent true values without measurement biases or errors. The other half $X_{post} \in \mathbb{R}^p$ are ...
3
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0answers
2k views

One inflated beta regression with random effects using GAMLSS

I am new to modelling percentage data, and I would be greatfull for some advice. I have proportion data (0,1] on a percentage of money sent by Player B to Player A. Participants received an amount of ...
2
votes
2answers
52 views

Is it possible to use location-scale family distributions for mixed effects modeling?

Is it possible to use location-scale family distributions for mixed modeling or generalized estimation equations? The only location-scale family package I know of is GAMLSS in R which is for additive ...
2
votes
1answer
763 views

Mann Whitney test, unequal sample sizes, different=shaped continuous proportions plus many zeros

I was hoping someone could help, I am comparing proportional data in to two different groups. One group has a sample size of 22 and the other 530. The data are not normally distributed and have ...
2
votes
1answer
24 views

GAMLSS Random Effect Coefficients

How do I extract the coefficients of my random effects in a Gamlss model? Let's take a simple example of a sample of individuals with intercepts which are normally distributed. Additional normally ...
2
votes
1answer
128 views

How was the pdf of the generalized gamma distribution in GAMLSS reparametrized?

I am trying to bring together the definition of the Generalized Gamma distribution in R-package GAMLSS by Rigby and Stasinopoulos and the general definition of the Generalized Gamma distribution, ...
2
votes
1answer
2k views

Maximum likelihood estimation under heteroskedasticity (and relation to OLS)

I have a question about MLE and how it relates to OLS. I know how to relate OLS and MLE when the noise is normal and homoskedastic. I can apply the same reason for heteroskedastic noise. My question ...
2
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0answers
745 views

Random effects in gamlss

I have a question regarding the gamlss package. I am attempting to fit a mixed effects model using the Befa Inflated distribution as follows ...
2
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0answers
514 views

How to build valid GAMLSS models?

Sorry for the following basic questions but it is important for me to get a feedback for my approach. I would like to create reference values for children in form of percentile curves (also called Z-...
2
votes
0answers
851 views

fitting mixture of bimodal distribution

I am trying to fit my data with a bimodal distribution using two beta distributions, however it seems to me that the two peaks are not captured very well. The reason that I notice from the data is ...
2
votes
0answers
166 views

Comparing categorical variable importance across groups; zero and one beta regression

I am attempting to compare behavioral responses across two species (one native and one invasive). Predictors run the range of types including continuous (size), discrete (day of trial) and ...
2
votes
0answers
1k views

Beta regression with random effects in R: different results in GAMLSS vs. glmmADMB

I am trying to fit a beta regression model to some repeated-measures data. I fit the model both with the function glmmadmb() in the ...
2
votes
0answers
345 views

Interpretation of Generalized Inverse Gaussian regression with GAMLSS

Background on my project: I am comparing proteins (nodes) between a network representing protein interactions in metastatic patients v/s another network representing protein interactions in non-...
2
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0answers
425 views

Assessing the accuracy of zero-inflated beta regression models

I have fitted a zero-inflated beta regression model to my data in R, using the gamlss package. However, I am unsure of how to assess the fit of the model to my data, i.e. finding a coefficient of ...
1
vote
3answers
266 views

How to choose correct distribution in R

I want to plot a probability distribution. I know the mean and think that a normal distribution would be a poor description of my beliefs. I either assume that the values smaller (or larger) than my ...
1
vote
2answers
1k views

Stepwise model selection using Generalized Akaike Information Criterion

I run a series of models using gamlss stepGAIC() model selection. The problem that I have is that in gamlss, ...
1
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2answers
320 views

Nonlinear regressor in GLM link function

Try to reproduce Robert E. McCulloch and Ruey S. Tsay’s paper Nonlinearity in High-Frequency Financial Data and Hierarchical Models with local market data. the paper uses GLM to model high-frequency ...
1
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1answer
479 views

Negative global deviance in gamlss?

What does a negative global deviance in gamlss mean? From their book "Flexible Regression and Smoothing", draft is here: http://www.gamlss.org/wp-content/uploads/2015/07/...
1
vote
1answer
419 views

How to model heteroscedasticity and get the coefficients?

I would like to model heteroscedasticity or better, the standard deviation of the mean as a function of x and retrieve the coefficients that says something about how standard deviation behaves with ...
1
vote
1answer
75 views

Is there a hypothesis test that tells us whether we should use GAM vs GLM?

Is there a hypothesis test that's ideally uniformly most powerful or metric that tells us whether we should use GAM vs GLM? Does there exists some kind of metric i.e. AIC/BIC or loglikelihood to ...
1
vote
1answer
240 views

Smoothing spline with dependent coordinates in R

I have a series of patients in whom I have measured the value of a certain blood quantity at several time points. However, the time points vary a lot and the number of measurements range between 2 and ...
1
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0answers
9 views

To what degree can distribution fitting of a response variable inform GLM family and link selection?

This is more of a theoretical question. I have a response variable that is best described by the Box-Cox Power Exponential distribution, but there is no way to really "run a GLM" with this information ...
1
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0answers
39 views

R gamlss - fitting and simulating lognormal response

I believe I am making a mistake in parametrization in this case. My goal is fit a lognormal model to data using gamlss in R, then simulate from that fitted model. ...