A discrete, univariate distribution modelling the number of ${\rm Bernoulli}(p)$ trial successes until a specified number of failures occur.

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2
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1answer
156 views

Negative-binomial why the answer is 0.288?

In a negative-binomial experiment with three independent trials, if I want the probability for 2 successes before the first failure. The probability of each trial is 0.6. ...
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0answers
7 views

Random parameter Negative Binomial Code for WinBUGS/OpenBUGS [on hold]

Can anyone help me by providing a sample code for random parameter negative binomial model for WinBUGS/OpenBUGS? I need to model crash count data with Random Parameter NB model. A sample code consist ...
2
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1answer
41 views

Poisson and NB results

i did a regression with poisson model, and since the dependant variable is overdispersed (0.13) , i have also tried negative binomial. The problem is that my explanatory variable "repeated partner" is ...
0
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0answers
20 views

Negative Binomial Regression 0 Problem

I am dealing with a count data set. I am trying to predict the amount of purchasers per day by the amount of previous purchasers for different products, counting the amount of purchases per day. ...
1
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1answer
25 views

glm.nb fails to converge when adding one zero

I have a problem where glm.nb (R version 3.1.0, MASS version 7.3.33) converges on some data, but adding only one 0 it does not converge any more. This is the data ...
0
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1answer
14 views

Standard error of Poisson and negative binomial regression

In Poisson and negative binomial regression, the response is assumed have Poisson and negative binomial distributions respectively. When we test the significance of the parameter $\beta$, which is ...
0
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0answers
11 views

Can I use SAS Copula procedure or Matlab copulafit to fit count data (Poisson or Negative Binomial)

I want to simulate data (x,y) with dependency using copula. Matlab has the function for t copula, Clayton, Frank, and Gumbel bivariate Archimedean copulas. But I am not sure if these functions could ...
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0answers
19 views

Multiple starting value/convergence warnings when running glm.nb in R

I'm running a negative binomial GLM in R. Running the model with the pooled dataset works just fine, but I'm encountering several warning messages when I attempt to run the same model for some of the ...
0
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0answers
25 views

WinBUGS/JAGS code for calculating Bayesian p-value from negative binomial model

I have a working negative binomial model written in BUGS code, but am not sure about the appropriate Bayesian p-value code to test goodness of fit. Specifically, I would like to calculate Pearson's ...
1
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0answers
19 views

How to model the following dependent variable? [closed]

If I got a dataset which the (count data) dependent variable has the following distribution, how should I model it? I am aware of the zero inflated model and the negative binomial model, but are ...
2
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1answer
36 views

Exploring effect of treatment on count data

I've collected data on animal visitation at four different points in time. The four time points represent the total animal visitations over a three day period, i.e. 3 days of monitoring at four ...
2
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1answer
24 views

Need code for sampling negative binomial with non-integer $r$

I'm trying to write code (in C) to sample from a negative binomial distribution parameterized by $r,p$, where $r$ is not necessarily integer (also called Polya distribution). I've found a number of ...
3
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0answers
58 views

simulating birth death process with random numbers from negative binomial

I am trying to generate random deviates for the population size at time $t$ for a birth-death process with constant birth and death rates per individual and initial size $N_0 \gt 0$. For the simple ...
2
votes
1answer
82 views

Is it meaningful to calculate predicted marginal effects of a count data model with an interaction effect?

In a little regression model of mine, I estimate the following formula a a negative binomial regression type (it would hold for a Poisson regression as well): $$ y = \beta * var1 + \gamma * var1 * ...
2
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1answer
36 views

Finding how many times I need to perform an action before I have an x% chance of a specific outcome in r

Non-specific question: There is an action that can be performed that has multiple outcomes. Each outcome has a different probably, p, of occurring. How many times, n, do I need to do the action before ...
1
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1answer
87 views

Choosing reasonable parameters for a negative binomial distribution

My data is a list of observations and a count for each observation. The data is overdispersed, the mean is ~1,200 and the variance is ~18,000,000. I want to use a negative binomial model to assign ...
0
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0answers
44 views

Zero Inflated Poisson or Negative Binomial Regression model in Panel Data

I am using the Stata version 13.1. My data is count in nature and also it is a balanced panel. However, my data suffers from the problem of excess zeros and also suffers the problem of overdispersion. ...
0
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0answers
46 views

Negative binomial mixed effect model for repeated measures with R - prediction and plotting

I have a dataset to analyze in which a response was recorded at the ends of months 1,3,4,5,6 in 187 patients. All patients had the responses recorded in each week, and all patients started a treatment ...
0
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1answer
22 views

Random Coefficient Negative Binomial Model

I have a crash count data and i want to build a random coefficient negative binomial model in R. The dependent variable will be the crash counts and covariates will be Lane width, AADT, shoulder width ...
2
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0answers
43 views

Modeling discrete count data with a gamma distribution

I've encountered a statistical model in which discrete count data are modeled with a gamma distribution (supported on nonnegative reals). The model relies on the property of the gamma that a sum of ...
1
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0answers
45 views

Negative binomial regression: Different results between the glm y x, (nbinomial 1) link(log) and glm y x, (nbinomial ml) link(log) Stata command?

I'm running a negative binomial regression. I found big differences in the results* if I compute with the glm y x, (nbinomial 1) link(log) and glm y x, (nbinomial ml) link(log) (for Stata) command. ...
0
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0answers
23 views

Upon transforming coefficients, how do I transform SE, z value and Pr(>|z|)?

From a Negative Binomial regression, I obtain the following coefficients: ...
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0answers
49 views

Predicted number of events from xtnbreg, fe make no sense

I am trying to compute the number of predicted events from a fixed effects negative binomial regression model in Stata. I run the model first using random effects, then using fixed effects, and ...
0
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0answers
40 views

Adding a square root link function to an overdispersed negative binomial GLM

I'm analyzing nematode count data (80 data points) from a randomized block design in which I have two factors with both four levels (Plant and Inoc). The data show heavy overdispersion when analyzed ...
2
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0answers
31 views

Specifying distribution in generalized estimating equation GEE

GEE allows you to identify the distribution of the outcome variable and appropriate link function. How do you make this selection in a longitudinal model where the distribution changes in time. An ...
3
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0answers
72 views

Modelling flight delays with negative values

Modelling flight delays with negative values I am working on a model to predict whether a flight will be delayed. The data consists of some explanatory variables for flights from a specific airport. ...
2
votes
1answer
55 views

Poisson for percentage data if values are low?

I have percentage data for diet per area (example here.....) I have no data on the individuals contributing to this diet, only for the population as a whole for each area. I want to assess ...
1
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0answers
21 views

Zero-inflated negative binomial regression: 0 probability of a count greater than 0

Zero-inflated negative binomial regression assumes 0s are generated by two processes: a group whose counts are generated by a negative binomial regression and a group who have a "0 probability of a ...
3
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2answers
132 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 ...
0
votes
1answer
36 views

Distribution of number of Bernoulli trials before some large number of sucess [duplicate]

We repeatedly make an experiment where we count the number $n$ of Bernoulli trials of known probability $p$, until some number of successes $s$ is reached. I'm willing to restrict to $p<0.01$ and ...
1
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2answers
136 views

hurdle model with negative binomial distribution of counts - error message and model selection

I'm working with over-dispersed count data, which is zero inflated (~2/3 zeros). I've fit a hurdle model using hurdle from ...
0
votes
1answer
79 views

Computing repeatability from overdispersed zero-inflated negative binomial GLMMM in R

I'm trying to compute repeatability of a count response variable from a Generalized linear mixed model with multiple fixed effects and individual ID as a random effect. I'm dealing with both ...
3
votes
1answer
305 views

R glmer.nb output. How to get $\hat{\theta}$?

I would like to obtain estimated $\theta$ from glmer.nb function in lme4 package. In my understanding this function fits the model: $$ Y_{ij}|\boldsymbol{B}_{i}=\boldsymbol{b}_i \overset{ind.}{\sim} ...
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0answers
32 views

Does negative binomial regression assume sample independence?

I'm working with a negative binomial multiple regression and I'm wondering about the assumption of spatial independence of samples. White and Bennetts (1996) say that the assumption of spatial ...
0
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0answers
34 views

Trending Residuals in Negative Binomial Panel Regressions with Patent Data

A commonly faced problem for researchers working with patent data is that we need to work with negative binomial models because our dependent variable is an overdispersed count variable. I am using ...
0
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0answers
58 views

Modelling count data: mean-variance relationship

I have fit a poisson, quasi poisson, and negative binomial model to some count data. To ensure that I have valid models, I am checking that the following assumptions are satisfied: No ...
0
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0answers
65 views

choosing between 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. I would know whether there is a practical ...
4
votes
1answer
240 views

Feasibility of Negative Binomial Spatial Regression

I have a set of crime count data where it appears that the data take on a negative binomial distribution. I have had some success converting the dependent variable (a crime count) into a rate and then ...
0
votes
1answer
37 views

Regression formula for negative binomial with random effects

I am doing a negative binomial regression with random effects. I have Panel data on 23 countries ($i$) across 28 years ($t$), with one dependent, one independent and three control variables. I do ...
1
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0answers
33 views

what is the meaning and purpose of modeling a data?

Background: I collected a whole years access logs of my website, counted visit frequency for every user, and the numbers of user at each unique frequency, I got a distribution: $n_w \tilde\ D_w(f_w ; ...
0
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0answers
38 views

Reference on interpretation of similar observed values and average adjusted predictions

I analyzed the association between a count dependent variable (DV) and a dummy independent variable (IV) (coded 0 and 1) ...
2
votes
0answers
46 views

Did the Eggenberger-Pólya (1923) paper derive the negative binomial distribution with real-valued parameter?

The negative binomial distribution can be derived in many ways, but two famous ones are due to Greenwood & Yule (1920) and Eggenberger & PĆ³lya (1923). Greenwood & Yule assumed unobserved ...
1
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0answers
56 views

Count Panel Data Event Study

Can anyone suggest a lecture/paper/textbook that covers an event study (eg. exogenous policy change) using count time-series (or penal) data? Or alternatively, just a general guideline as to what ...
6
votes
0answers
245 views

Overdispersion and modeling alternatives in Poisson random effect models with offsets

I have run into a number of practical questions when modeling count data from experimental research using a within-subject experiment. I briefly describe the experiment, data, and what I have done so ...
1
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1answer
54 views

Simulating Negative Binomial Arrivals

I am building a simulation. I want to generate arrivals according to a negative binomial process. The data will show the minute of each "customer" arrival and look something like the following: ...
0
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0answers
25 views

Convergence of distributions implies convolution (with itself) converge?

If 2 distributions converge in the limit, then do their convolutions also converge? e.g. I can show that for the Geometric distribution with random variable $T$, the scaled version with parameter ...
0
votes
1answer
48 views

What is the relationship between theta and size in negative binomial distribution?

In negative binomial regression glm.nb(y~x), I got a parameter theta and two coefficients? And then I want to use dnbinom(x, size, prob, mu, log = FALSE) to calculate the predicted probability. can ...
0
votes
1answer
187 views

Interpreting negative binomial regression with log transformed independent variables

My independent variables were highly skewed, so to normalise the distribution they were log transformed. Also since there were zeros in the data, I've added + 1 to transform the variables. This is ...
0
votes
0answers
163 views

Negative Binomial Regression model; algorithm did not converge

I am using R to run some negative binomial regression models. For model 1 I have the number of network in-degrees as the dependent variable, and Twitter followers, friends and number of Twitter ...
1
vote
1answer
264 views

Compare poisson and negative binomial regression with LR test

My question is related to the question Compare negative binomial models. I have some difficulties understanding UCLA guide in http://www.ats.ucla.edu/stat/r/dae/nbreg.htm (I am using ...