Questions tagged [gamlss]
Generalized additive models for location, scale and shape (GAMLSS).
65
questions
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1answer
38 views
can a normal distribution have negative deviance?
I'm using GAMLSS to model a variable as normally distributed with mean and SD as linear functions of some parameters. Sometimes GAMLSS gives me negative global deviances, but in my limited ...
1
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0answers
8 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 ...
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0answers
28 views
Standard deviation of outcome in gamlss model with random intercepts in mean
I'm interested in a simple random-intercepts model:
$$Y_{ij} = \alpha_0 + \gamma_i + \epsilon_{ij}$$
where $\gamma_i \sim N(0, \sigma_{\gamma}^2)$ independently of $\epsilon_{ij} \sim N(0, \sigma_{\...
1
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0answers
34 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. ...
1
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1answer
71 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 ...
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0answers
12 views
When to use location-scale family general additive models with censoring versus parametric survival models?
When to use location-scale family general additive models with censoring (gamlss.cens) versus parametric survival models, i.e. weibull, exponential, etc? implemented i.e. in survreg of the survival ...
2
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2answers
49 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 ...
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 ...
6
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2answers
390 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
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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 $x$...
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0answers
20 views
How to calculate Z-scores using gamlss IG distribution
I am having difficulty calculating Z-scores using the values generated from a gamlss model that used the 'IG' (inverse Gaussian) distribution. The calculation for generating Z-scores using LMS data is ...
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0answers
106 views
Confidence interval fit around GAMMA and BETA distribution
So currently I am using the new GAMLSS package and have plotted my model as shown in the photo. The blue line is my estimate (which I want to use at my point of estimate) when attempting to create a ...
2
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1answer
126 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, ...
1
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0answers
716 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
...
1
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2answers
303 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 ...
3
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0answers
844 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 ...
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1answer
285 views
This is the right way to use dummy variables on GAMLSS package? [closed]
I want to identify if the response variable on the example data-set below is different between A and B groups.
...
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0answers
505 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-...
5
votes
1answer
282 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
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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 ...
1
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0answers
289 views
What is the correct way to fit sigma.formula in gamlss() to add a per-dependent variable variance?
I have data in the format:
| organism | treatment | replicate | response |
| --- | --- | --- | --- |
| A | X | 1 | 20 |
| A | X | ...
0
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0answers
46 views
Zero-inflated model does not produce zeroes in fitted values? [duplicate]
I have used GAMLSS to fit a zero-inflated model. However, when I then turn around and FIT that model, it produces absolutely no zeroes at all (even though the data used to fit the model is about 40 % ...
5
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0answers
256 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 ...
1
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0answers
68 views
Zero-inflated model underestimates the number of zeroes due to “near zero values”
I am using GAMLSS. The data looks like this:
So, I tried a zero-inflated beta model (beta because data lies in the [0,100] interval, and so I just divided by 100).
The estimates I got using GAMLSS ...
1
vote
1answer
470 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/...
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1answer
27 views
Articles that work with covariates for mean, variance, and correlation simultaneously
Does anyone know of articles in which, in addition to modeling the mean parameter, are also modeled the variance and correlation parameters? I know the double generalized linear model, but they only ...
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0answers
126 views
What does 'additive framework' mean?
What does it signify in the context of non-linear relationships between multiple explanatory variables and dependent variable?
Just looking for an intuitive explanation.
In the context of GAMLSS ...
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 ...
1
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0answers
402 views
Why do different negative binomial regression functions produce different coefficients, p-values
I have a dataset consisting of number of mutations per person. Covariates I think may be related are age and source of the DNA sample. I want to determine whether the disease the person has ...
9
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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 ...
2
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0answers
128 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 ...
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0answers
989 views
What is Mu in zero/one beta inflated models? (gamlss (BEINF))
I am estimating a zero/one inflated beta regression model with gamlss (family BEINF). My dependent variable is [0,1] with a lot of 0s, quite some 1s, and some values in between. This means I assume ...
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1answer
406 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 ...
2
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0answers
841 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 ...
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 ...
0
votes
1answer
321 views
Analyzing reaction time data by implementing GAMM analyses with non-normal distribution parameters
I have two questions, a conceptual one and a practical one (that are closely related). And just as a note, I'm not super familiar with this level of stats (much more comfortable with simple linear ...
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 ...
8
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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 ...
9
votes
1answer
865 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 ...
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0answers
226 views
How to extract LMS constants from gamlss
I am trying to extract LMS constants from a gamlss object. I have the following gamlss object, where the best fitting family is the BCT.
...
2
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0answers
162 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 ...
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-...
2
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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 ...
1
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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 ...
2
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0answers
342 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-...
3
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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 ...
0
votes
2answers
1k views
Confidence intervals with gamlss package
My question regards the use of the gamlss package. I am using gamlss package to fit a dataset to a logistic function. There is ...
4
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1answer
737 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?
...
6
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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 ...
2
votes
1answer
758 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 ...
