similar to: undefined symbol: Rf_rownamesgets

there is my code,  expect return value  is a data frame but R say it is list: SEXP Julia_R_MD_NA_DataFrame(jl_value_t* Var) {  SEXP ans,names,rownames;  char evalcmd[4096];  int i;  const char* dfname="DataFrameName0tmp";  jl_set_global(jl_main_module, jl_symbol(dfname), (jl_value_t*)Var);  //Get Frame cols   sprintf(evalcmd,"size(%s,2)",dfname);  jl_value_t*

Dear listers, a few days ago I asked a question about a problem I had with a C function programmed by myself to be called from R. Thanks to your help, I have been able to look a bit further into it, so now I can be a bit more specific when telling what happens. The fact is that, when my C function finishes its execution (after calling it via the ".C" interface), R seems ok but

Hi , I am asking too many questions , sorry for that . I am creating a data frame in C itself , reading a table . The data frame calling code looks like this ====================================== *PROTECT(dfm=lang2(install("data.frame"),df));* *SEXP res = PROTECT(eval(dfm,R_GlobalEnv));* UNPROTECT(2); return res; ================================== It works fine , now the problem

Hello, I think there is an inconsistency in the handling of the compact form of the row.names attributes. When n is the number of rows of a data.frame, the compact form is c(NA_integer_,-n), as in: > d <- data.frame(x=1:10) > .Internal(inspect(d)) @104f174a8 19 VECSXP g0c1 [OBJ,NAM(2),ATT] (len=1, tl=0) @103a7dc60 13 INTSXP g0c4 [] (len=10, tl=0) 1,2,3,4,5,... ATTRIB: @104959380

Below x1, x2 and x3 all have the same data and all have the same value for row.names(x); however, the internal values of their row.names differ. The internal value of row.names is c(NA, -4L) for x1, c(NA, 4L) for x2 and c("1", "2", "3", "4") for x3; nevertheless, identical regards x1 and x2 as identical while x3 is not identical to either of x1 or x2. Is

I have code and documentation that don't match, but R CMD check didn't flag it. in mspath.R mspath <- function(formula, # formula with observed Markov states ~ observation times (required) qmatrix, # matrix of 1s and 0s with indices of allowed transitions (diagonal is ignored) (required) misc = FALSE, ematrix = NULL, # matrix

Now available on CRAN. Package: mspath Title: Multi-state Path-Dependent Models in Discrete Time Description: Functions for fitting path-dependent (non-Markov) multi-state models to categorical processes observed at arbitrary times, optionally with misclassified responses, and covariates on transition or misclassification rates. Uses discrete-time approximation. Based on the Jackson's

Now available on CRAN. Package: mspath Title: Multi-state Path-Dependent Models in Discrete Time Description: Functions for fitting path-dependent (non-Markov) multi-state models to categorical processes observed at arbitrary times, optionally with misclassified responses, and covariates on transition or misclassification rates. Uses discrete-time approximation. Based on the Jackson's

The cran2deb archives target testing. I just pulled a package from them onto a stable system; the library loaded but said > library(akima) Warning message: package 'akima' was built under R version 2.10.0 Are this and other packages likely to work correctly with different R's (2.7 in the case of stable)? How well are they likely to work with a backported R? The R version would

I can't tell from the docs ("Writing R Extensions" 1.9.1) exactly what environment the tests, examples, and vignettes that R CMD check tries to run are in. In particular: 1) how do I get the package loaded? 2) how do I access data in the data/ directory? 3) where is the material in the other directories? (e.g., has inst/ material been installed? where?) Apparently (section 1.3)

I'm having trouble getting correct help output in some circumstances for a package I've created. Though this is not an issue with the current R, I would like my package to work with previous ones as well. I'm looking for suggestions about how I could rework my .Rd file so that it will work with prior R's. In particular, R 2.7 is in the latest stable release of Debian, so I'd

I've attached a script I wrote that pulls all the setGeneric definitions out of a set of R files and puts them in a separate file, default allGenerics.R. I thought it might help others who find themselves in a similar situation. The "situation" was that I had to change the order in which files in my package were parsed; the scheme in which the generic definition is in the

I'm in the process of converting some S3 methods to S4 methods. I have this function : setGeneric("enrichmentCalc", function(rs, organism, seqLen, ...){standardGeneric("enrichmentCalc")}) setMethod("enrichmentCalc", c("GenomeDataList", "BSgenome"), function(rs, organism, seqLen, ...) { ... ... ... })