Hi - I was trying to estimate a model in eiR and it kept giving an error message. As a check, I tried running the default example, and - it crashed in the same way. Looks like some issue in the code. See the complete transcript below from installation to attempting to estimate the model for the "sample" data. thanks,
Ken
Prof. Kenneth Benoit
Head of Methodology Institute
London School of Economics and Political Science
Houghton Street
London WC2A 2AE
Tel. +44 207 9556812
kbenoit(a)lse.ac.uk
http://kenbenoit.net
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> install.packages("ei", type="source", repos="http://r.iq.harvard.edu", dependencies=TRUE)
trying URL 'http://r.iq.harvard.edu/src/contrib/ei_0.9310.tar.gz'
Content type 'application/x-gzip' length 835710 bytes (816 Kb)
opened URL
==================================================
downloaded 816 Kb
* installing *source* package ‘ei’ ...
** R
** data
** demo
** inst
** preparing package for lazy loading
** help
*** installing help indices
** building package indices ...
*** tangling vignette sources ...
‘ei.Rnw’
** testing if installed package can be loaded
* DONE (ei)
The downloaded packages are in
‘/private/var/folders/3_/7s7qq3wx08b8htzt5l9sdm6m0000gr/T/RtmpPCkwG2/downloaded_packages’
> library(ei)
Loading required package: mvtnorm
Loading required package: msm
Loading required package: tmvtnorm
Loading required package: Matrix
Loading required package: lattice
Attaching package: ‘Matrix’
The following object(s) are masked from ‘package:base’:
det
Loading required package: stats4
Loading required package: gmm
Loading required package: sandwich
Loading required package: zoo
Attaching package: ‘zoo’
The following object(s) are masked from ‘package:base’:
as.Date, as.Date.numeric
Loading required package: ellipse
Loading required package: plotrix
Loading required package: MASS
Loading required package: ucminf
Loading required package: cubature
Loading required package: mnormt
Loading required package: foreach
Loading required package: iterators
Loading required package: codetools
foreach: simple, scalable parallel programming from Revolution Analytics
Use Revolution R for scalability, fault tolerance and more.
http://www.revolutionanalytics.com
> data(sample)
> dbuf <- ei("t","x","n",data=sample)
Maximizing likelihood
Importance Sampling..
> summary(dbuf)
Error in matrix(abounds(ei1), nrow = 2) :
could not find function "abounds"
>
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