similar to: beta-binomial

Hello, I am trying to get the output from the numerical simulation of a system of ordinary differential equations for a range of values for three parameters. I am using the ode() function (deSolve package) to run the numerical simulation and apply() to run the simulation function for each set of parameter values. I am having trouble getting the apply() function to work. Here is an

Hello, I am using rbetabinom ( to generate beta binomial random variables) function available in the "emdbook"package written by Professor. Ben Bolker for my research study. I have no questions with this function. However, I am looking for the theoretical method/algorithm of the function "rbetabinom " . Morris (1997), American Naturalist 150:299-327 is given as the reference

the version 2 parser thinks I have unnecessary braces, but I can't find any. False positive or am I missing something? If a false positive, is there any way to work around the warning? * checking Rd files against version 2 parser ... WARNING Warning: ./man/dbetabinom.Rd:32-34: Unnecessary braces at ?{p(x) = % (C(N,x)*Beta(N-x+theta*(1-p),x+theta*p))/% Beta(theta*(1-p),theta*p)}?

Dear R users I would like to simulate underdispersed Poisson and binomial distributions somehow. I know you can do this for overdispersed counterparts - using rnbinom() for Poisson and rbetabinom() for binomial. Could anyone share functions to do this? Or please share some tips for modifying existing functions to achieve this. Thank you very much for your help and time Shinichi

Hi, My application spans 2 (or more) databases for some very specific reasons... My models are working fine, even dynamically establishing connections as needed at runtime, and spanning relationships across the databases (which really impressed me). The problem is, I can''t seem to force Units for these models (that use a secondary db) to load their fixtures into and use the

Hello, I am interested in fitting a generalized nonlinear regression (gnlr) model with negative binomial errors. I have found Jim Lindsay's package that will do gnlr, but I have having trouble with the particular model I am interested in fitting. It is a threshhold model, where below a certain value of one of the parameters being fitted, the model changes. Here is a sample: Cones:

When I try to make icecast, I get an error stating "/usr/bin/ld: cannot finf -lssl". I'm pretty sure I have all the libs I need. I was able to install icecast 1.3.12 through urpmi, but I want the newer version. Is there something I can do to resolve this? --- >8 ---- List archives: http://www.xiph.org/archives/ icecast project homepage: http://www.icecast.org/ To unsubscribe

Hi I want to do simulation on quasi-binomial distribution with some covariates. Does anyone have an idea how to do that? [[alternative HTML version deleted]]

I have some data which I am trying to fit with a negative binomial distribution. I have found the glm.nb function from MASS. I have reason to believe that the mean parameter mu depends on certain factors, and that the shape parameter theta depends on others. If, say, the factors are P and Q, it might be that mu ~ P:Q and theta ~ P (where mu ~ P:Q means that mu is a function of the pair (P,Q))

Hi, With help from Oleg we got the right patches applied and NFS working well. Maximum performance was about 60 MB/sec. Last week that dropped to about 12.5 MB/sec and I cannot find a reason. Lustre clients all obtain 100+ MB/sec on GigE. Each OST is good for 270 MB/sec. When mounting the client on one of the OSSs I get 230 MB/sec. Seems the speed is there. How can NFS and Lustre be tuned

Dear R users, [in case the format of email is changed or you dont finf it easy to understand, i have attached a text file of my question] i have the data in the following format and i want to convert it in the format given at the end. Ta ans Sa are the names of certain cities. there are 69 cities in my data. column 1 is representing station name (i am writing the data of only two cities for

Hello all friends! I have downloaded the latest ezstream (0.2.0) for Windows version, but I have faced some issues... First of all, on the installation process, it neither makes the desktop icon as it says it would do, nor creates a program group folder on the startup menu. Anyway, I try to finf on my Program Files folder and run in DOS mode the ezstream.exe I want to ask if I can grab the

Dear all, my apologies if I am posting a silly question - but I couldn't find any helpful information on this elswhere. In the R FAQ, version 1.8-1, there is a section "5.2 How can add-on packages be installed?", but it only gives information for Unix users. How can I install an add-on package under Windows? (Specifically, I have downloaded the "rmeta" package from CRAN.)

My sincerest apologies, as this is a very elementary problem, but I have searched through archives and FAQs and on the web, and I am at the end of my own resources. I need to do analysis of a spatial point process occuring with four counties, using spatstat. I've had no trouble importing the shapefiles, but I can't seem to figure out what I need to do in order to use the boundary as an

Take a look at this output from lsof: smbd 11490 0 8u REG 3,3 55296 1136647 Maintenanc.fp5 afpd 31010 0 2u REG 3,3 3207 1136655 auction - envelope.rtf afpd 31010 0 5u REG 3,3 4156 1136656 Word Work File L 1 afpd 31010 0 8u REG 3,3 55296 1136647 Maintenanc.fp5 smbd 31386 0 9u REG 3,3 4156 1136656 Word Work

R -users -- I am new to R and trying to create Jim Lindsay's Nonlinear Regression and Repeated Measures libraries. I have tried R CMD INSTALL file.tgz R says... ERROR: cannot extract package from file.tgz I have also tried build. Any tips? Cheers, Dan =-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-=-= Dan Powers Associate Professor, Sociology University of Texas at

The search at www.r-project.org mentioned a function "gauss.hermite{rmutil}". However, 'install.packages("rmutil")' produced, 'No package "rmutil" on CRAN.' How can I find the current status of "gauss.hermite" and "rmutil"? Thanks, Spencer Graves

Dear R users, I am trying to find a package that can estimate an autoregressive model for discrete data. I am imagining a Poisson or Gamma process in which the mean (say mu) follows a process such as mu_t = a + b*x + c*mu_{t-1} Suppose I have data on the time-series Poisson outcomes and x and would like to obtain ML estimates for b and c. Does anyone know of a package that can do this

Hi R-help, Is there such a thing as a function in R for fitting a GLM where the response is distributed as a Beta distribution? In my case, the response variable is a percentage ([0,1] and continuous). The current glm() function in R doesn't include the Beta distribution. Thank you for any help on this topic. Sincerely, Sharon K?hlmann

Hello R-helpers, I would like to fit a non-linear function to data (Discrete X axis, over-dispersed Poisson values on the Y axis). I found the functions gnlr in the gnlm package from Jim Lindsey: this can handle nonlinear regression equations for the parameters of Poisson and negative binomial distributions, among others. I also found the function nls2 in the software package