similar to: generate random sample from ZINB

Hello, 1. After I generate a 100x50 matrix by x3<-matrix(0,100,50);for (i in 1:100) {x1<-rpois(50, mu[i]);x2<-x1; x2[runif(50)<.01]<-0; x3[i,]<-x2}, 2. I want to calculate means and sample variances of each row and create a new matrix 100x2; 3. I then want to repeat above procedure 500 times so that eventually I will have 500 100x2 matrices. Would someone mind helping me to

Dear list, I would like to fit a negative binomial regression model as described in "Byers AL, Allore H, Gill TM, Peduzzi PN., Application of negative binomial modeling for discrete outcomes: a case study in aging research. J Clin Epidemiol. 2003 Jun;56(6):559-64" to my data in which the response is count data. There are also 10 predictors that are count data, and I have also 3

Hi r-users,   I would like to solve for z values using newton iteration method.  I 'm not sure which part of the code is wrong since I'm not very good at programming but would like to learn.  There seem to be some output but what I expected is a vector of z values.  Thank you so much for any help given.   newton.inputsingle <- function(pars,n) {  runi    <- runif(974, min=0, max=1)

Sorry bit of a Newbie question, and I promise I have searched the forum already, but I'm getting a bit desperate! I have over-dispersed, zero inflated data, with variance greater than the mean, suggesting Zero-Inflated Negative Binomial - which I attempted in R with the pscl package suggested on http://www.ats.ucla.edu/stat/R/dae/zinbreg.htm However my data is non-integer with some pesky

Dear R users, I'm wanting to sample from the negative binomial distribution using the rnegbin function from the MASS library to create artificial samples for the purpose of doing some power calculations. However, I would like to work with samples that come from a negative binomial distribution that includes only values greater than or equal to 1 (a truncated negative binomial), and I

Hi r-users,   I hope somebody can help me with this code. I would like to solve for z values using newton iteration method.  I 'm not sure which part of the code is wrong since I'm not very good at programming but would like to learn.  There seem to be some output but what I expected is a vector of z values.  Thank you so much for any help given.   newton.inputsingle <-

Dear all, I am modeling the incidence of recreational anglers along a stretch of coastline, and with a vary large proportion of zeros (>80%) have chosen to use a zero inflated negative binomial (ZINB) distribution. I am using the same variables for both parts of the model, can anyone help me with R code to compute overall marginal effects of each variable? My model is specified as follows:

Dear all.. I have a respon variable y. Predictor variable are x1, x2, x3, x4, x5 (1) What is the syntax to get paramater estimation of ZINB Model by Newton Raphson (not BFGS) (2) What syntax to plot probability of observed & predicted of ZINB Thx. Regards Krist. [[alternative HTML version deleted]]

Hello, I am working with zero inflated models for a current project and I am getting wildly different results from R's zeroinfl(y ~ x, dist="negbin") command and Stata's zinb command. Does anyone know why this may be? I find it odd considering that zeroinfl(y ~ x, dist="poisson") gives identical to output to Stata's zip function. Thanks, --david [[alternative

Buenas tardes, Estoy estimando un modelo binomial negativo de ceros inflados (ZINB) utilizando el comando zeroinfl() del paquete pscl. Al ejecutarlo me da el siguiente aviso: Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred ¿Sabéis que significa y si puedo usar el modelo aún con ese aviso? ¿Los coeficientes son fiables? Muchas gracias, Miriam

Hi all-- We are planning an intervention study for adolescent alcohol use, and I am planning to use simulations based on a hurdle model (using the hurdle() function in package pscl) for sample size estimation. The simulation code and power code are below -- note that at the moment the "power" code is just returning the coefficients, as something isn't working quite right. The

Buenas tardes, ¿Cómo interpretarías el intercepto que da R en un modelo de ceros inflados? Por un lado en la parte de conteo tengo un intercepto de -4.2 y en la parte de ceros de 102, ambos salen significativos (***). ¿Qué me dirían? Gracias

Dear users, Does anyone have any idea how to generate standardised beta coefficients for a ZINB model in R to compare which explanatory variables are having the greatest impact on the dependent variable? Thanks, Jeremy [[alternative HTML version deleted]]

Hi, I am Olga Viedma. I am running a Zero-inflated negative binomial (ZINB) multi-level model using MCMCglmm package. I have a doubt. Can I use the "Liab" outputs as fitted data, instead of the predicted values from "predict"? The liab outputs fit very well with the observed data, whereas the predicted values are so bad. Thanks in advance, Olga Viedma D . Olga

Hi R-Users! I fitted a negative binomial distribution to my count data using the function glm.nb() and obtained the calculated parameters theta (dispersion) and mu. I would like to simulate values from this negative binomial distribution. Looking at the function rnbinom() I was looking at the relationship between the two possible parametrizations of the negative binomial and found that for this

Muchas gracias por la respuesta. He mirado y los coeficientes no son altos pero sí tengo una gran cantidad de ceros en la variable dependiente (más del 90%). Sin embargo, al incluir otro tipo de variables independientes no me da ese aviso, dejando la misma variable dependiente. ¿Cómo podría utilizar stan/rstan de forma sencilla para diagnosticar el modelo? Muchas gracias El Lun, 9 de Abril de

¿Quieres decir que para un nivel de una variable categorica todas las observaciones de la variable respuesta sean ceros? Gracias El Lun, 9 de Abril de 2018, 19:59, Carlos J. Gil Bellosta escribió: > ¿Podría ser que para algún nivel de alguna variable independiente > categórica solo hubiese ceros? En ese caso, casi seguro, aparecería ese > tipo de warning. > > El lun., 9 abr. 2018 a

I have not included the previous postings because they came out very strangely on my mail reader. However, the question concerned the choice of minimizer for the zeroinfl() function, which apparently allows any of the current 6 methods of optim() for this purpose. The original poster wanted to use Newton-Raphson. Newton-Raphson (or just Newton for simplicity) is commonly thought to be the

Can someone show me how to specify zero inflated poisson and zero inflated negative poisson models in R? I would like to replicate the example given in Long (1997: Regression Models for Categorical and Limited Dependent Variables) in Chapter 8.5 (pp. 242-247). TIA Dirk ************************************************* Dr. Dirk Enzmann Criminological Research Institute of Lower Saxony

Hi All. I'd like to generate a sample of n observations from a k dimensional multivariate normal distribution with a random correlation matrix. My solution: The lower (or upper) triangle of the correlation matrix has n.tri=(d/2)(d+1)-d entries. Take a uniform sample of n.tri possible correlations (runi(n.tr,-.99,.99) Populate a triangle of the matrix with the sampled correlations Mirror the