similar to: Missing values in argument of .Fortran.

Dear all, I coded a function called u.glm u.glm <- function (x,ahi,age,bmiz,gender) { library(nortest) lil.rslt <- lillie.test(x) if (lil.rslt$p.value >0.05) { cat("Logtrans=0, lillie=",lil.rslt$p.value,"\n") xmodel<-glm(x~ahi+age+bmiz+as.factor(gender)) summary(xmodel) confint(xmodel) } else { cat("Logtrans=1,

Sorry guys, but I chose a really stupid name before (no "reference classes"). Hope it's okay to re-post. Cheers, Janko >>> ORIGINAL MESSAGE <<< Dear list, Is it possible to update or reassign '.self' with an image of '.self' (e.g. a locally stored .Rda file) from within a method? I know that this might sound akward, but here's the use

Hi the list, I am writing a R function that call a C function. The C function needs integers but I do not manage to give a NA integer as argument : --- C code --- void essai(int *t){ Rprintf("\nT0=%i T1=%i T2=%i T3=%i",t[0],t[1],t[2],t[3]); } --- R --- boub <- c(1,2,3,4) .C("pour",as.integer(boub),NAOK=TRUE) # T0=1 T1=2 T2=3 T3=4[[1]] # [1] 1 2 3 4 boub <-

Rusers, I am trying to append multiple .csv files of different dimensions (but # of columns are the same for all .csv files). I do have .csv files whose names are CA1.csv ~ CA100.csv. CA means california and 1 means the first file. So what I have been doing (after googling how to append by row multiple files) was: cleanup_data<-function(state,count) { out<-matrix() for (i in 1:

dear list, since matrix manipulations is often of interest in statistical computations, i'd like to get a working example of using Lapack for regression. However, i run into an error. My matrix-lapack-example.c file: #include <R_ext/Lapack.h> void reg(const char* trans, const int* m, const int* n, const int* nrhs, double* a, const int* lda, double* b, const int*

Hi, I'm using R to treat a table (with a lot of missing values) with Rulefit. The matter is when I use the command rfmod. Actually, I don't know how to deal with the error message. I don't know were "true" or "false" is missing. Someone can help me? Thanks The following part is the script I used with the error at the end. platform = "windows" rfhome

R-2.9.0/include/R_ext/Arith.h has: int R_IsNA(double); /* True for R's NA only */ int R_IsNaN(double); /* True for special NaN, *not* for NA */ int R_finite(double); /* True if none of NA, NaN, +/-Inf */ #define ISNA(x) R_IsNA(x) /* True for *both* NA and NaN. The first and last lines are contradictory - if R_IsNA is true only for NA, not NaN, then ISNA should be the same.

I have sort of an emergency question for the list. One of my professors for an S-Plus intensive class distributed a function to produce partial regression plots. I need to run it under R, because I'm doing the homework on my home computer with a modem; hence I don't have the speed required to emulate X-Windows and run S Plus off one of the campus servers. Bottom line: I'm using R.

I am trying to understand the function acf stats:::acf shows me the function I am having trouble understanding the usage "$acf" in the following acf <- array(.C(R_acf, as.double(x), as.integer(sampleT), as.integer(nser), as.integer(lag.max), as.integer(type == "correlation"), acf = double((lag.max + 1L) * nser * nser), NAOK =

Dear list: I am interested in the following sort of problem, as is found frequently in the field of QSAR. I have biological activity as a function of chemical structure, with structure defined in a categorical manner in that the SUBSTITUENT is the levels of the POSITION factor. For example, data from Kubinyi (http://www.kubinyi.de/dd-12.pdf) for this type of analysis is presented as follows:

Hi people, I am new in this list and could not find a FAQ for it in particular, furthermore I could not find my question answered in the official R FAQ or docs. I have simply something like this: > f<-approxfun(data[,1],data[,2]) and f is: > f function (v) .C("R_approx", as.double(x), as.double(y), as.integer(n), xout = as.double(v), as.integer(length(v)),

Full_Name: Naoki Takebayashi Version: 0.65.0+R-release.diff (Oct 6, 1999) OS: Linux/Alpha Submission from: (NULL) (129.79.224.171) This will fix the "problem 2 (crash in fft)" in Bug ID #277 On Linux/Alpha, make check failed because R could not handle the following example in base-Ex.R ##___ Examples ___: # The Old Faithful geyser data data(faithful) : : ## Missing values: x <-

I was hoping that there might be some way to attach significance code like the ones from summary.lm to a dataframe. Anyone know how to do something like that. Here is the function i'd like to add that functionality to: add1.coef <- function(model,scope,test="F",p.value=1,order.by.p=FALSE) { num <- length(model$coefficients) add <- add1(model,scope,test=test) sub <-

tabulate has .C("R_tabulate", as.integer(bin), as.integer(length(bin)), as.integer(nbins), ans = integer(nbins), PACKAGE="base")$ans The implementation of R_tabulate has if(x[i] != R_NaInt && x[i] > 0 && x[i] <= *nbin) and so copes with (silently drops) NA. Perhaps the .C could have NAOK=TRUE? This is useful in apply'ing tabulate to

> On Fri, 2017-10-20 at 14:01 +0000, brodie gaslam via R-devel wrote: > > I'm thinking of this passage: > > > > > Logical values are sent as 0 (FALSE), 1 (TRUE) or INT_MIN = > > > -2147483648 (NA, but only if NAOK is true), and the compiled code > > > should return one of these three values. (Non-zero values other > > > than INT_MIN are

Dear list, I have a series of data points which I want to approximate with exactly two linear functions. I would like to choose the intervals so that the total deviation from my fitted lines is minimal. How do I best do this? Thanks! Kamila The information transmitted in this electronic communication...{{dropped}}

Hello!   I would like to sample 30 % of cases (with at least 1 value lower than 3) and among them I want to set all values lower than 3 (within selected cases) as NA (NMAR- Not missing at random). I managed to sample cases, but I don’t know how to set values (lower than 3) as NA.   R code:   x <-

Readers, According to the help '?approxfun', the function can be used to obtain the interpolated values. The following test was tried: > testinterpolation<-read.csv('test.csv',header=FALSE) > testinterpolation V1 V2 1 10 2 2 20 NA 3 30 5 4 40 7 5 50 NA 6 60 NA 7 70 2 8 80 6 9 90 9 10 100 NA >

There appears to be a mild bug, or at least a deficiency, in rnorm. The bug becomes apparent when one looks at extremes of the squares of the values generated by rnorm; rnorm is not generating quite enough extreme values. The R version that I am using is 1.4.1; I never got around to installing 1.5.0, and now since 1.5.1 is about to come out .... However, checking the 1.5.0 release notes

I'm wondering if WRE Section 5.2 should be a little more explicit about misuse of integer values other than NA, 0, and 1 in LGLSXPs.? I'm thinking of this passage: > Logical values are sent as 0 (FALSE), 1 (TRUE) or INT_MIN = -2147483648 (NA, but only if NAOK is true), and the compiled code should return one of these three values. (Non-zero values other than INT_MIN are mapped to