similar to: Any numeric differentiation routine in R for boundary points?

Hi, Could anyone tell me what is the command used in R to do 1. Differentiation 2. Newton Raphson method (Numerical Analysis in general...) Are there any packages separately for this? Thanks for your help! BR, Shubha [[alternative HTML version deleted]]

Dear list: Before going into my problem, R list has been awesome for me ...thank you for the help. I have a simple problem, however I could get a answer to it... #my data myseed <- c(1001:1030) gend <- function(x){ set.seed(x) var <- rep(1:4, c(rep(4, 4))) vary <- rnorm(length(var), 50, 10) mat <- matrix(sample(c(-1,0,1), c(10*length(var)), replace = TRUE), ncol = 10) mydat <-

Hi: I have a question about the R plot, I change the size of the y axis label from 1 to 2, but part of the word is missing as being cut. So I guess it is over the boudary of the R graphical setting. Would you please help me with it? How to change the boundary so that the full part of my y axis label will appear? Your help is highly appreciated! sincerely hang No pain no gain.

Hi everyone, I am writing a pass that finds all uses of global variables (my goal is to find the uses of strings, and strings are defined as global variables). So, I can iterate over global vars by for(Module::global_iterator gi = M.global_begin(), gend = M.global_end(); gi != gend; ++gi) ...... But if I use its def-use chain for(Value::use_iterator i = gi->use_begin(), e = F->use_end; i!=e;

Hi, I have a data frame: > class(B27.vec) [1] "data.frame" > head(B27.vec) AGE Gend B27 AgeOn DD uveitis psoriasis IBD CD UC InI BASDAI BASFI Smok UV 1 57 1 1 19 38 2 1 1 1 1 1 5.40 8.08 NA 1 2 35 1 1 33 2 2 1 1 1 1 1 1.69 2.28 NA 1 3 49 2 1 40 9 1 1 1 1 1 1 8.30 9.40 NA

On Fri, 2004-06-18 at 10:13, Chris Lattner wrote: > Module::gbegin/gend iterate over the global variables, and ::begin/end > iterate over the functions, some of which may be prototypes. This confused Vladimir and I remember it confusing me when I was reviewing LLVM core a few months ago. Would it be worthwhile to consider naming these globals_begin/globals_end and

Hi I am trying to recover the hessian of a problem optimised with box-constraints. The problem is that in some cases, my estimates are very close to the boundary, which will make optim(..., hessian=TRUE) or optimHessian() fail, as they do not follow the box-constraints, and hence estimate the function in the unfeasible parameter space. As a simple example (my problem is more complex though,

Chris Lattner wrote: > > And why isn't it possible to just make those functions known to LLVM? > > After all, *I think*, if this function is to be called, it should be > > declared in assembler, and so you have to pass some information abou > > those function to the code printer. (Of course, it's possible to just > > directly print the declarations, but

On Fri, 18 Jun 2004, Vladimir Prus wrote: > > actually exist in the LLVM module for the function. In particular, this > > would include any functions in a code-generator specific runtime library > > and malloc/free. The X86 code generator compiles floating point modulus > > into fmod calls, and 64-bit integer div/rem into runtime library calls. > > And why isn't

Chris Lattner wrote: > > Second, MO_ExternalSymbol is used for storing name of external > > variable/function, right? Why it's not possible to use MO_GlobalAddress, > > where returned GlobalValue* has isExternal set to true? The > > GlobalValue::getName would return the name of the symbol. > > Using the GlobalValue is certainly the preferred way if you have it.

Thanks Chris, but the method you mentioned is not what I want. Maybe I didn't make it clear. As you said, /runtime/libprofile is runtime library for the following function. llvm_start_func_profiling llvm_start_block_profiling llvm_start_basic_block_tracing llvm_trace_basic_block And those above functions can be inserted into basic block etc for getting profile. However, those

P.S. Here's an example of verifier code that can emit multiple messages: bool doFinalization(Module &M) { // Scan through, checking all of the external function's linkage now... for (Module::iterator I = M.begin(), E = M.end(); I != E; ++I) visitGlobalValue(*I);

On Fri, 18 Jun 2004, Reid Spencer wrote: > On Fri, 2004-06-18 at 10:13, Chris Lattner wrote: > > > Module::gbegin/gend iterate over the global variables, and ::begin/end > > iterate over the functions, some of which may be prototypes. > > This confused Vladimir and I remember it confusing me when I was > reviewing LLVM core a few months ago. Would it be worthwhile to

sure, that's reasonable. I'll make the patch but later this weekend .. bigger fish to fry :) Reid. On Fri, 2004-06-18 at 22:44, Chris Lattner wrote: > On Fri, 18 Jun 2004, Reid Spencer wrote: > > On Fri, 2004-06-18 at 10:13, Chris Lattner wrote: > > > > > Module::gbegin/gend iterate over the global variables, and ::begin/end > > > iterate over the

Hi, I used split.screen command to creaye 5 screens, 4 screens contain a plot each, the fifth screen is designated to a legend. I am having difficulties setting the dimensions of the screens in a way that would allow me to have the screen dedicated to the legend smaller. I end up with a very awkward aspect at the end: 4 small plots with a big space for the legend. The gend needs to be at

Could somebody share some tips on implementing multivariate integration and partial differentiation in R? For example, for a trivariate joint distribution (cumulative density function) of F(x,y,z), how to differentiate with respect to x and get the bivariate distribution (probability density function) of f(y,z). Or integrate f(x,y,z) with respect to x to get bivariate distribution of (y,z). Your

In some tests I am getting a difference in the 7th or 8th significant digit depending on whether I set DUP=T or DUP=F in the .Fortran call below. While this is not a huge error it is bigger than I would expect and may be a symptom of another problem. Any comments or suggestions? (R1.2.2 on Solaris.) Paul Gilbert _______ genD.ARMA <- function(model, data, d=0.01, eps=1e-4, r=6, warn=F){ n

Does anybody know of a function that implements the derivative (gradient) of the multivariate normal density with respect to the *parameters*? It?s easy enough to implement myself, but I?d like to avoid reinventing the wheel (with some bugs) if possible. Here?s a simple example of the result I?d like, using numerical differentiation: library(mvtnorm) library(numDeriv) f=function(pars, xx, yy)

Hi, I've been trying to use optim to minimise least squares for a function, and then get a guess at the error using the hessian matrix (calculated from numDeriv::hessian, which I read in some other r-help post was meant to be more accurate than the hessian given in optim). To get the standard error estimates, I'm calculating sqrt(diag(solve(x))), hope that's correct. I've found

Quick question: Which function do you use to calculate partial derivatives from a model equation? I've looked at deriv(), but think it gives derivatives, not partial derivatives. Of course my equation isn't this simple, but as an example, I'm looking for something that let's you control whether it's a partial or not, such as: somefunction(y~a+bx, with respect to x,