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...series of two variables in a lattice plot: xyplot(y1 + y2 ~ t, data=size, type="b") y2 has missing data for some of the observations and some points are therefore not connected. It would make theoretical sense to connect the points - is there a way of doing that? (Without filling the obserations using package 'zoo'). Thanks, Allan -- DrAllan Sikk Lecturer in Baltic Politics University College London, School of Slavonic and East European Studies 16 Taviton St, London WC1H 0BW, United Kingdom tel: +44 (0)20 7679 4872 http://www.homepages.ucl.ac.uk/~tjmsasi/ [[alternativ...

To whom it may concern, I am a new user to R and I need help in my if and for statements as I need a place marker. I would like to convert the following table: Observation | Variable 1 --------------------|------------- 1 | 10000 2 | A 3 | 631 Into : Observation| Variable 1 | Variable 1 Flag ----------------|------------------|------------------ 1 | 10000 | NA 2 | NA | A 3 | 631 | NA please

Hi, I just noticed that rpart behaves unexpectecly, when performing classification learning and specifying a loss matrix. if the response variable y is a factor and if not all levels of the factor occur in the observations, rpart exits with an error: > df=data.frame(attr=1:5,class=factor(c(2,3,1,5,3),levels=1:6)) > rpart(class~attr,df,parms=list(loss=matrix(0,6,6))) Error in

Dear all, We have an emergency quick-fix release, version 4.11.1 for NSD. NSD 4.11.1 is available: https://nlnetlabs.nl/downloads/nsd/nsd-4.11.1.tar.gz sha256 696e50052008de4fa7ab1d818d5b77eb63247eea2f0575114c9592ff9188a614 pgp https://nlnetlabs.nl/downloads/nsd/nsd-4.11.1.tar.gz.asc NSD version 4.11.0 had a serious bug in which applying updates to zones (and other modifications that require a

Two questions: I have a lot of data for which the last of each of the repeated individual obserations is censored. Apart from the suite in survival, which seems to be very complex to a new R user, is there any other simple function that exists in CRAN library (I have most of these but haven't found one!) that is essentially the same as lm() but with an additional censor argument (vector of -1,...