search for: hurdles

Displaying 20 results from an estimated 599 matches for "hurdles".

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2007 Sep 16
2
are hurdle logit-poisson model and posson model nested?
Dear Listers, I have a general statistical question. Are hurdle logit-poisson model and posson model nested? Thank you so much?
2009 Oct 23
3
opposite estimates from zeroinfl() and hurdle()
Dear all, A question related to the following has been asked on R-help before, but I could not find any answer to it. Input will be much appreciated. I got an unexpected sign of the "slope" parameter associated with a covariate (diam) using zeroinfl(). It led me to compare the estimates given by zeroinfl() and hurdle(): The (significant) negative estimate here is surprising, given
2018 Feb 16
1
hurdle model - count and response predictions
Hello, I'm using pscl to run a hurdle model. Everything works great until I get to the point of making predictions. All of my "count" predictions are lower than my actual data, and lower than the "response" predictions, similar to the issue described here ( https://stat.ethz.ch/pipermail/r-help/2012-August/320426.html) and here (
2013 Oct 18
1
hurdle model error why does need integer values for the dependent variable?
Dear list, I am using the hurdle model for modelling the habitat of rare fish species. However I do get an error message when I try to model my data: > test_new1<-hurdle(GALUMEL~ depth + sal + slope + vrm + lat:long + offset(log(haul_numb)), dist = "negbin", data = datafit_elasmo) Error in hurdle(GALUMEL ~ depth + sal + slope + vrm + lat:long + offset(log(haul_numb)), :
2005 May 04
1
Double hurdle model in R
I am interested in utilizing this so called "double hurdle" model in my study. We can write the model in the following way: if (z'a + u > 0 & x'b + e > 0) y = x'b + e, else y = 0 In the model, consumption y is the (left-) censored dependent variable. e and u are the normally distributed error terms. z'a is the participation equation and x'b is the
2008 Jun 05
1
GAM hurdle models
Hello, I have been using mgcv to run GAM hurdle models, analyzing presence/absence data with GAM logistic regressions, and then analyzing the data conditional on presence (e.g. without samples with no zeros) with GAMs with a negative binomial distribution. It occurs to me that using the negative binomial distribution on data with no zeros is not right, as the negative binomial allows zeros.
2012 Aug 02
0
predictions from hurdle model
I ran a negative binomial logit hurdle model and am now trying to plot the effects of a continuous predictor variable (the only variable in my model) on the count and zero component and the overall mean response. I'm confused because for some values, the predicted overall mean is higher than the mean of the non-zero counts (range of predicted overall means=2.2-11.0; range of non-zero count
2013 Jul 23
0
percent correctly predicted (PCP) zeros for hurdle model
Hello all, I am using the hurdle model for fitting my count data using the pscl package which is working fine. However, I am stuck with the problem of calculating the percent correctly predicted (PCP) zeros for hurdle model. The method I am trying to use to achieve this is 'hitmiss' in the pscl package (ref: http://www.inside-r.org/packages/cran/pscl/docs/hitmiss). When I do: >
2011 Jul 12
2
Deviance of zeroinfl/hurdle models
Dear list, I'm wondering if anyone can help me calculate the deviance of either a zeroinfl or hurdle model from package pscl? Even if someone could point me to the correct formula for calculating the deviance, I could do the rest on my own. I am trying to calculate a pseudo-R-squared measure based on the R^{2}_{DEV} of [1], so I need to be able to calculate the deviance of the full and null
2008 Sep 14
0
Question on glm.nb vs zeroinfl vs hurdle models
Good afternoon, I?m in need of an advice regarding a proper use of glm.nb, zeroinfl or hurdle with my dataframe. I can not provide a self-contained example, since I need an advice on this current dataset and its ?contradictory? results. So.... i have a dataset which contains 1309 cases and 11 variables, highly right-skewed and heavily zeroinflated (with over 1100 cases that have 0 value
2009 Sep 22
0
Question about the negative binomial hurdle model with random effect using REML.
Dear All, I am wondering about the fitting negative binomial(NB) hurdle model with random effect using REML estimation method in R. We can fit regular hurdle model without random effect using ML method as following. hurdle(pkg).... But, I couldn't figure out how I can fit NB hurdle model with random effect using REML in R. Please give me a tip. Thank you so much. Sincerely, SK
2011 Jun 14
2
How to run zero inflated mixed model and hurdle mixed model in R
Dear Mr. or Ms.,   I would like to use the R-software to run the zero inflated mixed model and hurdle mixed model. But I do not know how to do? Would you please tell me the code and data format?   I will be very appreciated if you can help me. Thank you very much.   Best regards,   Sincerely, Xiongqing Zhang [[alternative HTML version deleted]]
2012 Jan 17
2
pscl package and hurdle model marginal effects
This request is related to the following post from last year: https://stat.ethz.ch/pipermail/r-help/2011-June/279752.html After reading the thread, the idea is still not clear. I have fitted a model using HURDLE from the PSCL package. I am trying to get marginal effects / slopes by multiplying the coefficients by the mean of the marginal effects (I think this is right). To my understanding, this
2011 May 04
1
hurdle, simulated power
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
2008 Nov 06
0
Inference and confidence interval for a restricted cubic spline function in a hurdle model
Dear list, I'm currently analyzing some count data using a hurdle model. I've used the rcspline.eval function in the Hmisc-library to contruct the spline terms for the regression model, and what I want in the end is the ability to compute coefficients and confidence intervals for different changes in the smooth function as well as plotting the smooth function along with the
1999 Aug 06
0
FW: RE: First (well second) CODA hurdle problem
My reply seems not to have made it to either list 24 hours after I sent it, so I'm sending it again. Apologies if you get this twice (or 4 times if you're on both lists, or 6 times if you're John) Martyn -----FW: RE: [R] First (well second) CODA hurdle problem----- Date: Thu, 05 Aug 1999 09:40:01 +0200 (CEST) From: Martyn Plummer <plummer at iarc.fr> To: John Logsdon
2012 Jul 15
0
NaN in hurdle model please?
Simplify your model. Does your TandemRepeat have a lot of levels? Or is your sample size very small? Alain Dear all, I am fitting a hurdle model in the following way: HNB <- hurdle(chro ~ as.factor(TandemRepeat)| as.factor(TandemRepeat), data =data_negbin_fin, dist = "negbin") But the std. error for log(theta) = NA Count model coefficients (truncated negbin with log link):
2012 Aug 22
0
hat matrix for zeroinfl and hurdle objects
Hi, I am wondering if there is an easy way to access the hat matrix for zeroinfl and hurdle objects in the pscl library? Thanks, Chris [[alternative HTML version deleted]]
2009 Nov 29
1
Convergence problem with zeroinfl() and hurdle() when interaction term added
Hello, I have a data frame with 1425 observations, 539 of which are zeros. I am trying to fit the following ZINB: f3<-formula(Nbr_Abs~ Zone * Year + Source) ZINB2<-zeroinfl(f3, dist="negbin", link= "logit", data=TheData, offset=log(trans.area), trace=TRUE) Zone is a factor with 4 levels, Year a factor with 27 levels, and Source a factor with 3 levels. Nbr_Abs is counts
2011 Jun 01
3
Zero-inflated regression models: predicting no 0s
Hi all, First post for me here, but I have been reading on the forum for almost two years now. Thanks to everyone who contributed btw! I have a dataset of 4000 observations of count of a mammal and I am trying to predict abundance from a inflated-zero model as there is quite a bit of zeros in the response variable. I have tried multiple options, but I might do something wrong as every