# Questions tagged [zero-inflation]

Excessive 0's in a variable compared to a specified reference distribution. Regression approaches include zero-inflated models and hurdle (2-part) models. For count data, zero-inflated and hurdle models based on Poisson or negative binomial distributions are common (ZIP/ZINB and HP/HNB).

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### Diagnostic plots for count regression

What diagnostic plots (and perhaps formal tests) do you find most informative for regressions where the outcome is a count variable? I'm especially interested in Poisson and negative binomial models, ...
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### What is the difference between zero-inflated and hurdle models?

I wonder if there is a clear-cut difference between the so-called zero-inflated distributions (models) and so-called hurdle-at-zero distributions (models)? The terms occur quite often in the ...
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### How to model non-negative zero-inflated continuous data?

I'm currently trying to apply a linear model (family = gaussian) to an indicator of biodiversity that cannot take values lower than zero, is zero-inflated and is ...
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### Beta regression of proportion data including 1 and 0

I am trying to produce a model for which I have a response variable which is a proportion between 0 and 1, this includes quite a few 0s and 1s but also many values in between. I am thinking about ...
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### Dealing with 0,1 values in a beta regression

I have some data in [0,1] which I would like to analyze with a beta regression. Of course something needs to be done to accommodate the 0,1 values. I dislike modifying data to fit a model. also I ...
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### Is a "hurdle model" really one model? Or just two separate, sequential models?

Consider a hurdle model predicting count data y from a normal predictor x: ...
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### Why exactly can't beta regression deal with 0s and 1s in the response variable?

Beta regression (i.e. GLM with beta distribution and usually the logit link function) is often recommended to deal with response aka dependent variable taking values between 0 and 1, such as fractions,...
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### Can a model for non-negative data with clumping at zeros (Tweedie GLM, zero-inflated GLM, etc.) predict exact zeros?

A Tweedie distribution can model skewed data with a point mass at zero when the parameter $p$ (exponent in the mean-variance relationship) is between 1 and 2. Similarly a zero-inflated (whether ...
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### Regression predictions show far less variance than expected

New to R and fairly new to statistics - appreciate any input. In short, I'm trying to develop a predictive regression model but after fitting the model on training data, the output for my testing ...
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### Zero inflate models vs generalized mixture model

I am looking to compare the fit of a zero-inflated mixture model and a Poisson mixture model. The random effects in both models are different. Comparing the fitted values of both models ignores the ...
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### 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 ...
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### How to test for Zero-Inflation in a dataset?

I have a dataset which seems to have a lot of zeroes. I have already fit a poisson regression model as well as a negative binomial model. I would like to fit zero-inflated and hurdle models as well. ...
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### Fitting a zero-inflated negative binomial regression with R

In this thread, I laid out a problem involving fitting a model that attempts to use minor league baseball statistics to predict success at the major league level (explained in full in the thread). ...
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### Linear Regression With Groups vs. Points - Issue with Influence of Zeros

I have a data set with two columns, the first of which is to be used as a response variable and the second of which is to be used as a predictor variable. The predictor variable, however, is populated ...
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### Zero inflated distributions, what are they really?

I am struggling to understand zero inflated distributions. What are they? What's the point? If I have data with many zeroes, then I could fit a logistic regression first calculate the probability of ...
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### GLM with continuous data piled up at zero

I am trying to run a model to estimate how well catastrophic illnesses such as TB, AIDS etc affect spending on hospitalization. I have "per hospitalization cost" as the dependent variable and various ...
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### A model for non-negative data with many zeros: pros and cons of Tweedie GLM

I analyze technical measurement data with the aim of developing a forecasting model. The data is given as a non-negative time series (data per hour). The data looks quite wild and contain many zeros. ...
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### Zero-inflated Poisson regression Vuong test: Raw, AIC- or BIC-corrected results

I'm analyzing count data for a set of ten species and found that for the five species with highest detection rate, the zero-inflated poisson (ZIP) regression fits the data significantly better than ...
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### Zero-inflated two-part models for semi-continuous data

I am trying to study predictors of companies' pollution output of some specific chemicals. The data I am using have many 0's (i.e., the company did not pollute at all with those chemicals) and then ...
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### Count data with one factor level containing only zeroes

I have a simple poisson glm with one predictor that has three levels. Unfortunately, for one level my response, the variable has only counts of zero. I expected very low counts (perhaps a one or a two ...
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### Is there a distribution appropriate for a continuous variable skewed toward zero and able to include zero?

I am interested in modelling the impact of some environmental parameters on a concentration of measured phytoplankton pigment. The concentration of pigment is skewed so that low concentrations are ...
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### When to use Poisson vs. geometric vs. negative binomial GLMs for count data?

I'm trying to layout for myself when it's appropriate to use which regression type (geometric, Poisson, negative binomial) with count data, within the GLM framework (only 3 of the 8 GLM distributions ...
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### Poisson regression assumptions and how to test them in R

I would like to test in what regression fits my data best. My dependent variable is a count, and has a lot of zeros. And I would need some help to determine what model and family to use (poisson or ...
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### "Zero-inflated" predictors in regression?

I know that zero-inflated models (e.g. zero-inflated Poisson or negative binomial models) can be used for dependent variables. I also know that in general there are no assumptions for the independent ...
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### Proper use and interpretation of zero-inflated gamma models

Background: I am a biostatistician presently wrestling with a dataset of cellular expression rates. The study exposed a host of cells, collected in groups from various donors, to certain peptides. ...
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### Measure of "deviance" for zero-inflated Poisson or zero-inflated negative binomial?

Scaled deviance, defined as D = 2 * (log-likelihood of saturated model minus log-likelihood of fitted model), is often used as a measure of goodness-of-fit in GLM models. Percent deviance explained, ...
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### How can I set up a zero-inflated poisson in JAGS?

I am trying to set up a zero-inflated poisson model in R and JAGS. I am new to JAGS and I need some guidance on how to do that. I've been trying with the following where y[i] is the observed ...
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### Are a zero-truncated Poisson and basic Poisson nested or non-nested?

I've seen plenty that discusses whether a basic Poisson regression is a nested version of a zero-inflated Poisson regression. For instance this site argues that it is, since the latter includes extra ...
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### Zero-inflated count models in R: what is the real advantage?

For analysing zero-inflated bird counts I'd like to apply zero-inflated count models using the R package pscl. However, having a look at the example provided in the documentation for one of the main ...
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### Simulate from a zero-inflated poisson distribution

I am trying to simulate from observed data that I have fit to a zero-inflated Poisson regression model. I fit the data in R using zeroinfl() from the package ...
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### Zero Inflated Logistic Regression - Does This Exist?

I have a dataset with information belonging to medical patients (e.g. age, gender, height, etc.). Suppose that the response variable is whether or not the patient has a specific disease or not - thus, ...
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### Forecasting daily time series sales revenue with many zero entries

I have been trying to forecast the sales revenue of different product groups (the displayed sales revenue is aggregated over all products for each day e.g. smartphones with different prices as one ...
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### 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 ...
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### Forecasting daily time series with many zeros

I need to forecast a univariate time-series of sales data with the following characterica. It is a daily time-series Around 70-80 % of the date nothing is sold ($x_t = 0$) At the 20-30 % remaining ...
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### hurdle model with non-zero gaussian distribution in R

I have biomass data (continuous response variable). If sufficient data is collected, the log(Biomass) follows a normal distribution. However, I am separating the overall biomass by family (i.e., ...
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### Justification for using a zero-inflated negative binomial regression

I'm trying to describe in words why I used a zero-inflated negative binomial regression instead of an negative binomial regression: To model my data I used a negative binomial regression. However, as ...
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### How can I compare two zero inflated continuous datasets?

I have two zero-inflated datasets such as, dt1= 0, 0.1, 0.125, 0, 0, 1.25... dt2= 1.01, 0, 0, 0.25, 0,... I want to check the differences, like t.test for ...
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### Confused on how to interpret ZINB and Hurdle models

Below are a set of results from a zero-inflated (AIC = 64992.15; BIC = 65280.78) and hurdle model (AIC = 65141.73; BIC = 65430.36) for a dataset (>18000 obs) which describes the number of illicit ...
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### How to get p-values for the zero-inflated part of a model?

I am having a problem that I am not finding an answer anywhere online. I used glmmTMB to fit a mixed-model. My data is zero-inflated and I am including 3 variables in the zero-inflated formula. I was ...
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### Can Tobit model handle a clustered data with many zeros in a continues outcome? [duplicate]

I have a longitudinal data, with different follow-up number for individuals. I have considered measurements for each individual as a curve which I already smoothed them, then calculated the area under ...
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### Gamma hurdle model for continuous response?

I am modelling invertebrate.biomass ~ habitat.type * calendar.day + habitat.type * calendar.day ^ 2, with a random intercept of ...
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### Zero-inflated negative binomial mixed-effects model in R

Is there such a package that provides for zero-inflated negative binomial mixed-effects model estimation in R? By that I mean: Zero-inflation where you can specify the binomial model for zero ...
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### GAMM with zero-inflated data

Is it possible to fit a GAMM(Generalized Additive Mixed Model) for zero-inflated data in R? If not, is it possible to fit a GAM(Generalized Additive Model) for zero-inflated data with a negative ...
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### When should one use a Tweedie GLM over a Zero-Inflated GLM?

I have seen both Tweedie GLMs and Zero-Inflated (ZI) GLMs used in the field of ecology. Tweedie seems to have the benefit of not treating excess zeros separately, as is done using ZI regressions. ...
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### Type I and Type II negative binomial distribution in zero inflated negative binomial (ZINB) model

When is it appropriate to use a Type I versus Type II negative binomial distribution in a zero-inflated negative binomial distribution? I've found a Similar question, but without an answer I can ...
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### When to use zero-inflated poisson regression and negative binomial distribution

I have a fairly simple dataset looking at the relationship between the first nesting date of a bird in a given year (Date) and the birds overall fledgling production from that year (Fledge; count data ...
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### Does there exist zero-inflated linear regression?

I have a non-count data with huge number of zeros in the target variable. I need to fit a model being a mixture of Dirac delta function and normal distribution parametrized by mean $X\beta$ and ...
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