Displaying 20 results from an estimated 36 matches for "negbin".

2011 Feb 10

2

Comparison of glm.nb and negbin from the package aod

I have fitted the faults.data to glm.nb and to the function negbin from the
package aod. The output of both is the following:
summary(glm.nb(n~ll, data=faults))
Call:
glm.nb(formula = n ~ ll, data = faults, init.theta = 8.667407437,
link = log)
Deviance Residuals:
Min 1Q Median 3Q Max
-2.0470 -0.7815 -0.1723 0.4275 2.0896...

2007 Dec 12

1

Defining the "random" term in function "negbin" of AOD package

I have tried glm.nb in the MASS package, but many models (I have 250 models
with different combinations of predictors for fish counts data) either fail
to converge or even diverge.
I'm attempting to use the negbin function in the AOD package, but am unsure
what to use for the "random" term, which is supposed to provide a right hand
formula for the overdispersion parameter. I'm not even sure what this
statement means. Any advice you have would be greatly appreciated.
negbin(formula, random,...

2010 Feb 11

1

Zero-inflated Negat. Binom. model

...i.e. how well does chick size predict tape intensity?
Since I have a small sample size, I fit a zero inflated negat. Binomial (not
Poisson) model using the "pscl" package.
I built tried two models and got the outputs below.
> model <- zeroinfl(Int_Cesto ~ CAPI, dist = "negbin", EM = TRUE)
Call:
zeroinfl(formula = Int_Cesto ~ CAPI, dist = "negbin", EM = TRUE)
Count model coefficients (negbin with log link):
(Intercept) CAPI
-2.99182 0.06817
Theta = 0.4528
Zero-inflation model coefficients (binomial with logit link):
(Intercept)...

2011 Oct 26

2

gam predictions with negbin model

Hi,
I wonder if predict.gam is supposed to work with family=negbin()
definition? It seems to me that the values returned by type="response"
are far off the observed values. Here is an example output from the
negbin examples:
> set.seed(3)
> n<-400
> dat<-gamSim(1,n=n)
> g<-exp(dat$f/5)
> dat$y<-rnbinom(g,size=3,mu=...

2010 Feb 04

1

Zero inflated negat. binomial model

...g at the association between these two variables, i.e. how well does chick size predict tape intensity?
I fit a zero inflated negat. binomial model using the "pscl" package.
I built my model as follows and got the output below.
> model <- zeroinfl(Int_Cesto ~ CAPI, dist = "negbin", EM = TRUE)
> model
Call:
zeroinfl(formula = Int_Cesto ~ CAPI, dist = "negbin", EM = TRUE)
Count model coefficients (negbin with log link):
(Intercept) CAPI
-2.99182 0.06817
Theta = 0.4528
Zero-inflation model coefficients (binomial with logit link):
(Inte...

2013 Mar 15

0

Poisson and negbin gamm in mgcv - overdispersion and theta

...rsion parameter from a (Poisson) gamm?
I have not been able to extract residual degrees of freedom from M1.
2) How to manually estimate theta for a negative binomial gamm?
I would like to see if applying a negative binomial distribution with log link (model below) would solve the problem. However, negbin in gamm requires a known theta...
M2 <- gamm(Resp ~ s(Day, k=8) + s(Day, by=C, k=8) + Flow + offset(LogVol),
data=MyResp,
correlation = corAR1(form= ~ Day|Mesocosm),
family= negbin(THETA, link="log"))
3) And finally, can I somehow compare the mode...

2005 Jun 02

1

glm with variance = mu+theta*mu^2?

How might you fit a generalized linear model (glm) with variance =
mu+theta*mu^2 (where mu = mean of the exponential family random variable
and theta is a parameter to be estimated)?
This appears in Table 2.7 of Fahrmeir and Tutz (2001) Multivariate
Statisticial Modeling Based on Generalized Linear Models, 2nd ed.
(Springer, p. 60), where they compare "log-linear model fits to

2011 Sep 22

1

negative binomial GAMM with variance structures

...I am having some difficulty converting my gam code to a correct gamm code, and I'm really hoping someone will be able to help me.
I was previously using this script for my overdispersed gam data:
M30 <-gam(efuscus~s(mic, k=7) +temp +s(date)+s(For3k, k=7) + pressure+ humidity, family=negbin(c(1,10)), data=efuscus)
My gam.check gave me the attached result. In order to deal with my heterogeneity, I need to switch over to a gamm structure and use at least one, but possibly multiple, variance structures, and I am starting by applying varPower to my temperature covariate. (Efuscus i...

2005 Jun 30

1

RE : Dispersion parameter in Neg Bin GLM

Edward, you also can use the package aod on CRAN, see the help page of the function negbin.
Best
Matthieu
An example:
> library(aod)
> data(dja)
> negbin(y ~ group + offset(log(trisk)), ~group, dja, fixpar = list(4, 0))
Negative-binomial model
-----------------------
negbin(formula = y ~ group + offset(log(trisk)), random = ~group,
data = dja, fixpar = list(4, 0))...

2018 Feb 16

1

hurdle model - count and response predictions

...on-count-vs-response
).
Since the issue is the same (and not resolved), I'll just use the example
from the second link:
library("pscl")
data("RecreationDemand", package = "AER")
## model
m <- hurdle(trips ~ quality | ski, data = RecreationDemand, dist = "negbin")
nd <- data.frame(quality = 0:5, ski = "no")
predict(m, newdata = nd, type = "count")
predict(m, newdata = nd, type = "response")
The presence/absence part of the model gives identical estimates to a
logistic model run on the data. However, I thought that...

2011 May 04

1

hurdle, simulated power

...n function logit model
p0 <- exp(alpha0 + alpha1*trt)/(1 + exp(alpha0 + alpha1*trt))
### 0 / 1 based on p0
y1 <- as.numeric(runif(n)>p0)
### mean function count portion
mu <- exp(beta0 + beta1*trt)
### estimate counts using NB dist
require(MASS, quietly = TRUE)
y2 <- rnegbin(n, mu = mu, theta = theta)
### if y2 = 0, draw new value
while(sum(y2==0)>0){
y2[which(y2==0)] <- rnegbin(length(which(y2==0)), mu=mu[which(y2==0)],
theta = theta)
}
y<-y1*y2
data.frame(trt=trt,y=y)
}
#alpha0, alpha1 is the parameter for zero part
#beta0,beta1 is the parameter for...

2008 Mar 20

1

logLik calculations

Does the ?logLik? function applied to a ?glm? and ?glm.nb? (from MASS
package) calculate the complete log-likelihoods, or does it drop the
constant terms of the equation? (It?s not clear from the associated help
pages, and I?ve found no reference from searching the R help mailing list)
Thank you,
Kelly Young

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)), :
invalid dependent variable, non-integer values
When I do fit the same model with round(my dependent variable) the model works. Sorry for the stupid question but could anyone...

2010 Sep 03

2

Interactions in GAM

...h to prevalence (distribution=binomial) and to intensity (distribution=negative binomial):
gam(prevalence~s(length)+factor(year)+factor(area)+s(length,by=area)+s(length,by=year), family=binomial,data=X)
gam(intensity~s(length)+factor(year)+factor(area)+s(length,by=area)+s(length,by=year), family=negbin(c(1,10)),data=X)
The solution that I have seen to introduce an interaction "continuous covariate- continuous covariate" is using the function "te". Below, I show an example of my model with the interactions using "te" both to prevalence (distribution=binomial) and t...

2005 Mar 03

1

Negative binomial regression for count data

...(mean=2.8, variance=28) as well as in predictors, and there are a lot of zero's (zero-inflated).
The authors of that paper used PROC GENMOD in SAS 8.1. I wonder which of the following packages and tests to use in R to acheive such model for my analysis. Is there any tutorial available?
anova.negbin
Likelihood Ratio Tests for Negative Binomial GLMs
glm.convert
Change a Negative Binomial fit to a GLM fit
glm.nb
Fit a Negative Binomial Generalized Linear Model
negative.binomial
Family function for Negative Binomial GLMs
rnegbin
Simulate Negative Binomial Variates
theta.m...

2011 Sep 02

5

Hessian Matrix Issue

...irical estimates or sample moments
xbar<-mean(y)
variance<-(sum((y-xbar)^2))/length(y)
dbar<-variance/xbar
#sample estimate of proportion of zeros and zero inflation index
pbar<-length(y[y==0])/length(y)
### Simplified function #############################################
NegBin<-function(th){
mu<-th[1]
d<-th[2]
n<-length(y)
arg1<-n*mean(y)*ifelse(mu >= 0, log(mu),0)
#arg1<-n*mean(y)*log(mu)
#arg2<-n*log(d)*((mean(y))+mu/(d-1))
arg2<-n*ifelse(d>=0, log(d), 0)*((mean(y))+mu/ifelse((d-1)>= 0, (d-1),
0.0000001))
aa<-numeric(lengt...

2006 Jul 20

0

Convergence warnings from zeroinfl (package pscl)

...lly 0 occurred in: glm.fit(X, Y, family =
poisson()) >>
suggest that it did not converge. (See full output below.)
Could some possibly help me to interpret these results?
Thanks for your time,
Dan
> zip3=zeroinfl(count=round(modAbun*1000) ~ .,
+ x=~mod*intact,
+ z=~1,
+ dist="negbin",
+ trace=TRUE,
+ data=beetles)
Zero-Inflated Count Model
Using logit to model zero vs non-zero
Using Negative Binomial for counts
dependent variable y:
Y
0 10 11 14 17 19 21 23 25 28
31 33 34 37 40 42 46
1056 3...

2012 Dec 10

1

Marginal effects of ZINB models

...s of the model, can anyone help me with R code
to compute overall marginal effects of each variable?
My model is specified as follows:
ZINB <- zeroinfl(Tot.Anglers ~ Location + Season + Daytype + Holiday.not +
CPUE + ShoreType + Access + Source.pop + WindSpeed + offset(beat_length),
dist="negbin", data=anglers)
Many thanks,
Jeremy
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2005 Jan 26

2

Source code for "extractAIC"?

Dear R users:
I am looking for the source code for the R function extractAIC. Type the
function name doesn't help:
> extractAIC
function (fit, scale, k = 2, ...)
UseMethod("extractAIC")
<environment: namespace:stats>
And when I search it in the R source code, the best I can find is in (R
source root)/library/stats/R/add.R:
extractAIC <-

2013 Jun 04

1

Zero-Inflated Negative Binomial Regression

Hi!
I'm running a zero-inflated negative binomial regression on a large (n=54822) set of confidential data. I'm using the code:
ZerNegBinRegress<-zeroinfl(Paper~.|., data=OvsP, dist="negbin", EM=TRUE)
And keep getting the error:
Warning message:
glm.fit: fitted probabilities numerically 0 or 1 occurred
I've done enough reading about this error to realize that I have a linear separation issue, for which the solut...