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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35k views

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, ...
43k views

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 ...
9k views

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 ...
4k views

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: ...
14k views

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 ...
5k views

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 ...
4k views

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,...
4k views

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 ...
8k views

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). ...
2k views

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 ...
3k 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 ...
5k views

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 ...
134 views

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 ...
1k views

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 ...
12k views

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 ...
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 ...
7k views

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. ...
4k views

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 ...
5k views

“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 ...
871 views

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, ...
2k views

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 ...
4k views

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 ...
634 views

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 ...
5k views

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. ...
5k views

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 ...
1k views

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., ...
8k views

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 ...
16k views

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 ...
10k views

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 ...
2k views

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 ...
4k views

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 pscl, but I am having trouble figuring out ...
2k views

Enormous SEs in zero-inflated negative binomial regression

I have overdispersed count data where the outcome is events (occurrence of a rare disease) and the covariate of interest is season. The unit of analysis is the number of events occurring in a country-...
8k views

Correct glmer distribution family and link for a continuous zero-inflated data set

Data set details: Zeros are "real" (volume) Data set is heavily left skewed (even when zeros are excluded) Response is continuous (volume) Can anyone recommend a distribution family and link that I ...
2k views

Penalized regression with zero-inflated models

I'm currently building zero-inflated Poisson & negative binomial predictive models using the zeroinfl() function from the pscl package in R. Incorporating penalized regressions into my model to ...
1k views

Gibbs sampling with mixed prior using a Metropolis-Hastings step

My questions are about a sampling procedure for ﬁtting a Bayesian hierarchical model where one of the priors is a mixture distribution of discrete and continuous parts. The model is not my own but I ...
1k views

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 ...
2k views

Fitting a glm to a zero inflated positive continuous response

I'm trying to fit R glm's to data sets where the response is zero inflated positive continuous. This is an example data set ...
3k views

Zero inflated Poisson model

I am working to investigate association between environmental pollution and daily hospital admission due to various causes. This outcome data has excess zeros on days when there are no admissions ...
5k views

Response variable: percentage and too many zeros (zero inflated Poisson?)

I am analysing the effect of density (categorical), gonad mass (continuous) and temperature (continuous) on the percentage of acini spawning in a gonad. My replicate unit is a scallop. As my response ...
634 views

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. ...
1k views

Non-parametric test of difference for zero-inflated data

I have zero-inflated (~90% zeros) data which is distributed like the left-hand figure above (the right-hand figure shows how when log-transformed, the non-zero component of the distribution is ...
869 views

Zero-inflated Poisson regression

Suppose $\textbf{Y} = (Y_1, \dots, Y_n)'$ are independent and \eqalign{ Y_i = 0 & \text{with probability} \ p_i+(1-p_i)e^{-\lambda_i}\\ Y_i = k & \text{with probability} \ (1-p_i)e^{-\...
806 views

Imputation for a zero-inflated negative binomial mixed effects model

I am working with a dataset of repeated (x4) observations on 100 subjects. The outcome is zero-inflated and the data appears to be modelled well by a mixed effects zero-inflated negative binomial ...
1k views

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 ...
129 views

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 ...
1k views

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 ...
1k views

How can I fit a zero inflated poisson model with only offset (without coefficients)?

I have already got a poisson estimated lambda, and actual result y, and I would like to see if the model is good. To start with, I check if the dispersion is ...
651 views

glmmADMB- Pseudo R^2 and residual deviance criteria

I’ve been using glmmADMB to fit zero-inflated negative binomial models with a random effect (as far as I can tell, this is the only package that will allow me to do this). I have been trying to do ...