similar to: Unused Arguments Error Even Though I'm Using Them?

Hi I am trying this > x <- read.table("/home/kenji/1245/GDS1_2grps_.cls", header = F, skip = 2) > x <- read.table("/home/kenji/1246/MYCset.cls", header = F, skip = 2) Warning message: In read.table("/home/kenji/1246/MYCset.cls", header = F, skip = 2) : incomplete final line found by readTableHeader on '/home/kenji/1246/MYCset.cls' Here are the

On Wed, 8 Jan 2020, I?aki Ucar wrote: > On Wed, 8 Jan 2020 at 19:21, Toby Hocking <tdhock5 at gmail.com> wrote: >> >> Hi R-core, I was wondering if somebody could please add jsslogo.jpg to the >> R sources? (as I reported yesterday in this bug) >> >> https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17687 >> >> R already includes jss.cls which

Hi R-core, I was wondering if somebody could please add jsslogo.jpg to the R sources? (as I reported yesterday in this bug) https://bugs.r-project.org/bugzilla/show_bug.cgi?id=17687 R already includes jss.cls which is the document class file for Journal of Statistical Software. Actually, for the jss.cls file to be useful, it also requires jsslogo.jpg in order to compile JSS articles without

Dear R users, I don't know how to compute an exponential model like this: proc=a*exp(b*cls), or proc=a*exp(b*cls)+c*exp(d*cls). Please help me to solve this problem! Thank you! My data is: row.names proc cls 1 0.5 452.616206 0.5 2 1 255.864021 1.0 3 1.5 150.885316 1.5 4 2 86.289600 2.0 5 2.5 56.321559 2.5 6 3 39.504444 3.0 7 3.5 25.570308 3.5 8 4 5.382726 4.0 -- --- Catalin-Constantin

Hi all, I need to run c++ prgrams using lli. However, I find lli cannot handle the alias instruction correctly. Following is an example: ------------ example.cc ------------- #include <iostream> using namespace std; class cls { public: cls(); ~cls(); }; cls::cls() { cout << "constructor" << endl; }; cls::~cls() { cout <<

hi, I use R - 2.15(32bit), and want to make a code to clear a console. Actually, I used to run following code to do that but after update the version of R from 2.14 to 2.15, it doesn't work. cls <- function (t) { require(RDCOMClient) wsh <- COMCreate("Wscript.Shell") wsh$SendKeys("\f") invisible(wsh) } cls() or cls <-

Hello all! I have a problem to use a biexponential regression model: I use this code: n3<-nls(proc~SSbiexp(cls,a,b,c,d),data=bline) and this is the error message: Error in nls(y ~ cbind(exp(-exp(lrc1) * x), exp(-exp(lrc2) * x)), data = xy, : singular gradient My data is like this: structure(list(proc = c(387.177462830167, 508.090511433077, 321.836817656365, 151.226805860727,

Dear all, I''m trying this thing for a while but can''t figure out what am I doing wrong. Here is my sample function (which is similar to the original one, except for the hash, which is generated dynamically in the original one): module Puppet::Parser::Functions > newfunction(:am_running_oss, :type => :rvalue ) do |args| > > oss =

While building llvm & clang & libs by giving some optimization options to the building compiler, the following error happened: I think it is related to the passed -DCLS=64, because in file clang/lib/Frontend/Rewrite/RewriteModernObjC.cpp:6411 an enum member has the same name (CLS), so it does a macro-substitution with the passed value of CLS, ie. with 64, but which of course then breakes

Hello all! I have a problem with a double exponential equation. this are my data's> structure(list(proc = c(1870.52067384719, 766.789388745793, 358.701545859122, 237.113777545511, 43.2726259059654, 148.985133316262, 92.6242882655781, 88.4521557193262, 56.6404686159112, 27.0374477259404, 34.3347291080268, 18.3226992991316, 15.2196612445747, 5.31600719692165, 16.7015717397302,

I?ve been using this routine for several years. I?m sorry, I don?t remember where I got it. It works as it should, viz. it blanks the R console. But it requires package rcom and now that requires rscproxy. cls <- function () { require(rcom) wsh <- comCreateObject("Wscript.Shell") comInvoke(wsh, "SendKeys", "\f") invisible(wsh) } > cls()

On May 9, 2013, at 6:34 PM, Nick Lewycky <nlewycky at google.com> wrote: > I'm looking into how we can improve devirtualization in clang, and there a language in C++ feature I'd like to take advantage of which would let us perform elimination of more vptr loads. In this code: > > Cls *p = new Cls; > p->virtual_method1(); > p->method_changing_vptr(); //

Hello Again R Folks: I?m trying to clean up some code. Suppose I have an object like this: > str(test) List of 2 $ G:List of 2 ..$ cls:'data.frame': 101 obs. of 2 variables: .. ..$ V1: num [1:101] -0.0019 -0.0019 -0.00189 -0.00188 -0.00186 ... .. ..$ V2: num [1:101] 0.000206 0.000247 0.000288 0.000329 0.000371 ... ..$ rob:'data.frame': 101 obs. of 2

On 7/16/19 6:04 AM, Richard W.M. Jones wrote: > A Closure is a list of (usually one, but can be more) closures. In C > there is also a singe ‘void *user_data’ parameter which is passed by > the caller into the function and through as the first parameter of > each callback invocation. > > By grouping the previously separate Opaque and Callback* parameters > together we can

For a long time now I've been using a function: classed <- function (x, cls) { class(x) <- cls x } as a utility at the end other functions to set the class of an object and return the object. I've noticed examples where others have been doing a similar thing and I think it would be a useful addition to R base (unless there is already something there to do this - it

I'm looking into how we can improve devirtualization in clang, and there a language in C++ feature I'd like to take advantage of which would let us perform elimination of more vptr loads. In this code: Cls *p = new Cls; p->virtual_method1(); p->method_changing_vptr(); // uses placement new to legally change the vptr p->virtual_method2(); // invalid! Cls *q = p;

Hello, I am struggling to produce an MDS plot using the randomForest package with a moderately large data set. My data set has one categorical response variables, 7 predictor variables and just under 19000 observations. That means my proximity matrix is approximately 133000 by 133000 which is quite large. To train a random forest on this large a dataset I have to use my institutions high

Tim Northover via llvm-dev wrote on 06/19/2018 07:55 PM: > On Tue, 19 Jun 2018 at 18:22, U.Mutlu via llvm-dev > <llvm-dev at lists.llvm.org> wrote: >> I think such "reserved" names like CLS that can be passed to the compiler(s), >> should be avoided as identifiers for naming variables, constants, enum >> members, macros etc. > > Why are you passing

On 22 August 2015 at 19:20, Ilyas Arinov <arinov.ilyas at gmail.com> wrote: > I have to update pages twice now to see its content. > > --> --> > > Traceback (most recent call last): > File "/usr/lib/python2.6/site-packages/MoinMoin/request.py", line 1207, in > run > handler(self.page.page_name, self) > File >

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hello: I'm having problems with this line of code: X.lm <- lapply(names(d), function(x) lm(d["cls"] ~ d[x], data=d)) d[x] is what is giving trouble here, but I don't know exactly how to solve it. What I'm trying to do is to create a linear model from each column of the data frame 'd' to apply ANOVA later. Thanks