Variables that are counts (non-negative integers) often have an excess of zeroes. Zero-inflated regression models (e.g. zero inflated Poisson, zero inflated negative binomial) are designed to deal with this. Less commonly, continuous data can have this issue, and there is zero-inflated normal ...

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6 views

R mhurdle with same 2 predictors in 2 separate hurdles

My outcomes are zero-inflated but otherwise normal. I want to propose a model in which the very same predictors determine both whether the value is zero or non-zero, and separately from that, if ...
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1answer
53 views

Are my data zero inflated?

I'm building a function/package. If the users' entry data are zero inflated then the code will log-normalise them, process them, and reverse-log-normalise and bias-correct them afterwards. If they're ...
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0answers
21 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 ...
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0answers
12 views

Multiple regression with many zero values in DV, skewed data

I am not an expert, but I am trying to run a fixed effect multiple regression model in STATA. My data is panel data and has around 12000 observations, 348 districts over 36 months. My dependent ...
2
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0answers
44 views

Basic idea of zero inflated two part models(hurdel) and application to big data (machine learning)

I'm currently working on the data which has 90% 0s in response variable. Based on my research, it seems zero inflated models could be a solution to this. However, while I was reading related ...
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0answers
30 views

How to model overdispersed percentage data?

this is my first post so let me know if you need more information. This is a pretty general question for now, but I am not sure how to approach this. The data I have is from an ecological study. In ...
6
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3answers
157 views

GLM with 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. Now I have "per hospitalization cost" as the dependent variable and ...
0
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1answer
25 views

Problems with interpretation in zeroinflated models in R

My response variable is number of Fishing cat scats and I am using a zero-inflated poisson regression model to see the effect of the predictor variables on habitat use of Fishing cats. The predictor ...
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0answers
19 views

Limits of zero-inflated negative binomial in % of zeroes

What are the limits of a zero-inflated regression? Specifically, if more than 80% of the data is zeroes, is the ZINB still valid? What is a good rule of thumb or educated way to understand the right ...
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1answer
60 views

Zero inflated negative binomial with selection

I am looking for a Stata (or R/Matlab if there's no Stata) implementation of the model described by Greene (1994) (http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1293115). It is essentially a ...
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0answers
11 views

comparing same negative binomial models built with subset data

I have a dataset made our of several stacked datasets (one for each state). I want to check whether a zero inflated negative binomial model with data from an individual state is different from the ...
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2answers
134 views

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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1answer
47 views

“Zero-inflated continuous covariates”, Can they cause problems in logistic regression?

I pose a very similar question to this, although I felt the advice given does not apply to my particular situation; I am using logistic regression models for an animal habitat occupancy study, and ...
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0answers
27 views

how to fit a zero inflated NB distribution with large mu and sigma by fitdist + gamlss functions

I've been trying to figure out how to use gamlss.famliy Zero inflated functions (e.g. ZIP) on the data. A descriptive stat on my data is as follows; ...
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0answers
73 views

Outlier detection with ROBPCA for multivariate poisson/non-normal data

It is stated here[1] that we can use ROBPCA to detect outliers for multivariate data. After reading the manual ([2] page 12 : "multivariate normal model etc."), I think the ROBPCA method is also ...
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1answer
34 views

Interpretation of binomial parameters in zeroinfl in R

In the help page of zeroinfl, it says "a binary model is used that captures the probability of zero inflation." But it seems it is modeling the opposite of that ...
3
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1answer
158 views

Zero-inflation on steroids: choose among Poisson, negative binomial and zero-inflated regressions

I am struggling to fit alternative count models into my data. I guess my problem is just too many zeros. This is my data ...
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1answer
27 views

Interpreting ZINB - inflation model non-significant

I have a zero-inflated negative binomial model to a dataset (n = 47) with a over-dispersed dependent variable (...
2
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0answers
62 views

BRT predictions on zero-inflated gaussian fish abundances include negative results

hopefully someone can point me in the right direction here. I'm using boosted regression trees (BRT) to assess the relative importance of a number of environmental factors (sea bottom temperature, ...
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1answer
54 views

Correlations in count data

I have two count data variables X and Y that contain many zero values (90% in X, 60% in Y). I would like to check if a correlation exists between these variables, but I'm not sure how to proceed due ...
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0answers
45 views

Model choice for nonnegative and positive continuous right skewed outcome

I am trying to analyze a set of nonnegative continuous non-integer data (i.e. the data points are not counts) that are mostly between 0 and 3 whose distribution is highly right-skewed even after log ...
2
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1answer
87 views

Why NB and Poisson performs superior than ZIP, ZINB and Hurdle in presence of lots of zeros?

I am working on a data which contain nearly 80% of zeros and positive counts as large as 7. The dataset is very large, nearly 16,000 cases. It is a health related data. I have fitted ZIP, ZINB and ...
3
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0answers
28 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 ...
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2answers
135 views

Why are there no one-inflated count data models?

I am working on zero-inflated count data models using the pscl package. I am just wondering why there is no development of models for one-inflated count data ...
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1answer
131 views

Approaches to regression with zero inflated response

I have zero inflated response variable I am trying to predict. I am facing few issues applying different regression models that should correct for this. This is my 10,000 obs dataframe ...
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1answer
444 views

predict function and categorical variables in R

This is more of a general question about how the predict function treats categorical variables and how to interpret the output from predict. I have a zeroinfl model to predict the number of animals ...
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0answers
77 views

How can one test the assumptions of a zero-inflated negative binomial model in R?

I have fitted a zero-inflated model with a random effect using a negative binomial distribution in R, using the function glmmadmb. This is due to a large number of zeros and over dispersion. For a ...
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0answers
117 views

Suitable method for modelling (underdispersed?) count data with lots of zeros and long tail

I have a small data set of counts of bees. I tried a simple Poisson model without random effects but it was very overdispersed (3.95). When I fit a GLMM with random effects (using glmer in lme4) it ...
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1answer
71 views

not concave iterations on a zinb model

my name is vincenzo and i have that type of problem with zinb that you intorduce in this discussion (ZIP converges but ZINB does not. Should I drop this model?): the iterations continues to be not ...
2
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1answer
104 views

Comparing the distributions of two processes, one of which is constrained by zero

I have two continuous stochastic Markov processes: the concentration readout of two proteins in a cell over time. These are shown in this figure, where the blue line is the unbounded protein, and all ...
3
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2answers
180 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 ...
3
votes
0answers
332 views

Trouble finding good model fit for count data with mixed effects - ZINB or something else?

I have a very small data set on solitary bee abundance that I am having trouble analysing. It’s count data, and almost all the counts are in one treatment with most of the zeroes in the other ...
1
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1answer
58 views

How to calculate the expected zeros in a Poisson distribution?

I am modelling the nights spent at hotels (count data) fitting a few predictors in the model. I'd like to know how to calculate the expected number of zeros in this distribution, as I suspect that I ...
2
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0answers
21 views

Statistical test for zero valued variable

I am testing a product (liquid bag) for leakage and my primary variable is the amount of leakage in ml. I have a specification that states, on average, leakage must be below XXml. In total I tested 20 ...
3
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0answers
47 views

How to model continuous predictor variable, $x\ge0$, showing continuity “jump” at $x=0$?

I'm modeling hospital inpatient stays with a logistic regression model, and have encountered a number of predictor variables measuring # of outpatient care episodes which have an inflated number of ...
1
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1answer
150 views

Comparing two groups with many zeros

I am comparing the difference in time-activity-budgets of two populations of seabirds, those in the presence of ship disturbance and those not in the presence of ship disturbance. Focal animals were ...
0
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0answers
53 views

How to model zero-inflated continuous response using categorical predictors - preferably resulting in multiplicative parameters

I'm having trouble finding a suitable model for predicting the AVG value (revenue in cents) of a single click on a product on a large e-commerce site. (assuming a click leading directly to a purchase ...
3
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4answers
1k views

What is the difference between zero-inflated and hurdle distributions (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 ...
1
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2answers
238 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 ...
3
votes
1answer
168 views

Why am I not able to fit a zero inflated poisson distribution?

Following what is suggested here http://stackoverflow.com/questions/7157158/fitting-a-zero-inflated-poisson-distribution-in-r ...
0
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1answer
81 views

Defining a threshold for percentage data with high amounts of exact zeros

I am trying to analyse my biological data which is derived from flow cytometry and describes the percentage of cells with a certain property. Data is available for two conditions: once the cells ...
0
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0answers
89 views

How to interpret the coefficients for binormal part in zero-inflated regression?

use zeroinfl {pscl} I specified offset only for the poisson part. The regression estimate zeroes using regressor zeros ...
2
votes
1answer
82 views

Zero inflate models vs generalized mixture model

Hi 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 ...
0
votes
1answer
161 views

Undefined real result in a zero-inflated negative binomial

I have run a zero-inflated Poisson model in WinBUGS without problems, and now I am trying to run its equivalent negative binomial. However, I get an "undefined real result" trap message over and over. ...
0
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0answers
68 views

How to spot if model is zero inflated?

I'm running a linear regression. The response variable is a proportion, and has quite a lot of zeros. The predictor variable is normal distributed. My two variables look something like these: ...
1
vote
0answers
84 views

Zero-inflated negative binomial

I am trying to understand zero-inflated negative binomial regression. My impression is that if a zero-inflated negative binomial model does not contain any logit part, the model is identical to the ...
0
votes
0answers
194 views

Modelling zero-inflated percentage data in R

I have a response variable of percent cover of vegetation in a quadrat. I have tried to arcsine square this data as recommended in the Crawley R book but I am not getting good fit. The data is ...
2
votes
0answers
125 views

Log-linear or poisson model with R [closed]

I have a data.frame (myData) with 6 variables which are: ...
2
votes
1answer
146 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 ...
24
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2answers
2k 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, ...