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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1answer
71 views
Whether to incorporate zero inflation into model of binary variable on count variable?
I have a dataset comprising two groups with 1 continuous covariate (ratio scale). The dependent variable is a count variable. The distribution of the dependent variable looks like this:
I was ...
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0answers
32 views
Is there a R function that can give me parameter estimation of data following a zero inflated poisson distribution? [closed]
I have a series of numbers, I know it's from zero-inflated poisson distribution. Is there an R function that can give me the parameter values? For example, I used rzipois function in VGAM package to ...
3
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0answers
125 views
Mixed models and normally distributed random effects
I am attempting to analyze some data that includes 10 repeated measurements on 10 different samples. This would normally require using mixed models, and I have attempted to model these using ...
2
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1answer
70 views
What is the difference between a zero-inflated and a zero-truncated poisson?
I'm trying to make sense of a question which uses a zero-inflated poisson model given by:
$$
f(x; \lambda,\omega) = \begin{cases} \omega + (1-\omega)e^{-\lambda} &\mbox{if } x = 0 \ \ \ \ \ \ ...
2
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0answers
22 views
Searching for a model like ZIP, but to model three data-generating processes, not just two
What type of test would fit my data in this situation?
I'm measuring a count variable. Like in a zero-inflated poisson, I have numerous observations that are zeros because of a separate process. But ...
3
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1answer
173 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 ...
5
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2answers
573 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 ...
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73 views
How to model daily time-series data as a function of another variable where the predictor is often zero using R?
I have two correlated variables, x and y and I need to quantify the 'impact' of x on y (explained below).
The y variable has it's own weekly-seasonal pattern.
The x variable is weather related, so ...
2
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0answers
133 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 ...
4
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2answers
838 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 ...
1
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0answers
131 views
How to derive the probability mass function for Zero-inflated Poisson Distribution?
I am a maths student and I asked to derive the zero-inflated poisson distributon. I looked it up in the interent and I found the p.m.f. however I have no-idea why it looks the way it looks. Thank you ...
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1answer
609 views
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 ...
2
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1answer
164 views
Given count data with many zero observations, what is a reasonable amount of zero observations in the data?
I have sales data which records at what time (by second) and how many were sold. Therefore, the data is count data with around 90-150 sales during a 3-day period. If I agggregated it to the 10 minute ...
0
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0answers
96 views
Analyzing online sales where data are only produced when the sales is made
I am trying to model data on the number of online sales are made within a fixed sale period of 3 days. Data are generated only when the sale is made. I think for this kind of data I will be using a ...
6
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2answers
133 views
Experimental design & questions on use of generalized linear models
I have an ecological experiment for which I need to analyze bird count data. Here is the set up:
2 treatments (open/control), 3 regions. Not quite a full 3x2 factorial because in 2 regions there are ...
3
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0answers
128 views
Is splitting one hurdle model in two GLM/GAM models a valid approach?
I came across several publications dealing with overdispersed zero-inflated count data that "simply" modelled presence absence in one model and then postive counts in a second model. This led to two ...
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1answer
110 views
Derivation of a the log-likelihood for a regression model where the outcome is a mixture between Poisson and a point mass at zero
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} \ ...
6
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3answers
393 views
How to test/prove data is zero inflated?
I've got a problem that I think should be simple but can't quite figure it out. I'm looking at seed pollination, I have plants (n=36) that flower in clusters, I sample 3 flower clusters from each ...
3
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1answer
421 views
How to get standard errors from R zero-inflated count data regression?
The following code
PredictNew <- predict (glm.fit, newdata = Predict, X1 =X1, Y1= Y1,
type = "response", se.fit = TRUE)
produces a ...
3
votes
1answer
232 views
How do I interpret data from a 2x2 experiment with a floor effect that causes it to lack any variation in one cell?
I have performed a 2x2 experiment to measure the effects of two genetic factors on the occurrence and size of a rare birth defect. When an individual has the defect, we can measure its size (size is a ...
4
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1answer
2k views
Mean and variance of a zero-inflated Poisson distribution
Can anyone show how the expected value and variance of the zero inflated Poisson, with probability mass function
$$
f(y) =
\begin{cases}
\pi+(1-\pi)e^{-\lambda}, & \text{if }y=0 \\
...
4
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2answers
984 views
Proper use and interpretation of zero-inflated gamma models
Hello StackExchange users,
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 ...
3
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1answer
255 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 ...
3
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3answers
664 views
Fitting a probability distribution to zero inflated data in R
I am trying to learn how to fit a probability distribution to a vector of data, using the program R, but there are a lot of potential probability distributions to use! So my question is, how do I ...
4
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3answers
387 views
Zero inflated models - “true zero” vs. “excess zero”
I am trying to decide if zero inflated poisson is appropriate for my data vs. a Poisson hurdle model.
In background reading between the two I've run across a statement saying that a zero inflated ...
