[R] Using the digest and t distribution.
Hello R community, I have two questions: The first might be one of the silliest ever posted here and I apologize if I've missed some thing very obvious. It relates to using this digest. When I subscribed to the forum, I had chosen the digest option that bundles all mails every day into a single digest. Now, I posted a question a while ago on the logistic regression function and got no reply. After a while, I realized that it was probably bundled up in one of the digests. So, looked through them and found my question in Vol107, issue 16. My question was number 34 in it and some one had posted a solution to it which appeared in item number 42. However, when I scrolled down to the bottom of the digest, it went only up to 24. In any case, I've tried searching a a variety of other things and just can't find the solution posted to my question in the body (I couldn't even thank the solution provider). Can some one please tell me where I can find it and if there is an easy way to access particular mails sent to you. My second question is related to the fitting the t distribution with the fitdistr function. I am actually trying to fit it to the standard data set in the Ecdat package. Here is my code: library(ecdat) data(SP500) #Fitting a normal distribution runs just fine. fitdistr(SP500[[1]],normal) meansd 0.0004180994 0.0108610082 (0.0002058797) (0.0001455789) #But when I try the t: fitdistr(SP500[[1]],t) m s df 0.0005236326 0.0083937340 9.984297 (0.0001721041) ( NaN) ( NaN) There were 17 warnings (use warnings() to see them) #I get these NaN and warnings. Am I doing some thing wrong here? Also, if some one relies, could you please mark any reply to my personal ID as well (rohitpandey...@gmail.com)? -- Thanks in advance, Rohit __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Need help interpreting the logit regression function
Hello R community, I have a question about the logistic regression function. Specifically, when the predictor variable has not just 0's and 1's, but also fractional values (between zero and one). I get a warning when I use the glm(formula = ... , family = binomial(link = logit)) which says: In eval(expr, envir, enclos) : non-integer #successes in a binomial glm! I looked this up on a few forums and got the impression that I could go ahead and ignore this warning. If that is not so, please suggest another function that can be used (and no need to read further). But if this is usable, then the numbers are not making sense for me. What I am seeing is best explained through an example: #Setting up the data: c(1,1,0,0,1,1,0,1,1,0,0,0,0,1,1,0,0,0,0,1)-resp indep-rep(2:3,10) #Running the logistic regression: glm(formula = resp~as.factor(indep) , family = binomial(link = logit),na.action = na.pass) #Gives me: Coefficients: (Intercept) as.factor(indep)3 -1.692e-16 -4.055e-01 table(indep,resp) resp indep 0 1 2 5 5 3 6 4 Meaning that the odds for '2' to have a favorable outcome are 5/5 =1; and the odds for 3 are 4/6 = 0. And indeed, exp( -1.692e-16) = 1 and exp( -1.692e-16+-4.055e-01) = 0.66. But when I change all the 1's of the independent variable to 0.5, the odds should both be half of what they were before (right?). However, when I run the logistic function after doing this, resp[resp==1]=0.5 glm(formula = resp~as.factor(indep) , family = binomial(link = logit),na.action = na.pass) (Intercept) as.factor(indep)3 -1.0986-0.2877 Now, exp(-1.0986) = 0. and exp(-1.0986-0.2877) = 0.25. These are nothing like the previous odds halved. So, either I am using the function wrong or interpreting it wrong. Can some one please point me in the right direction.. -- Thanks in advance, Rohit __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] help with the maxBHHH routine
Hi Andrew, Ravi and Arne, Thank you so much for your prompt replies. I see that all of you mention the need for simple, reproducible code. I had thought of doing this, but the functions I was using for the observation level gradient and likelihood function were very long. I will paste them below here. Also, sorry for the ambiguity with the 1000's of observations and 821 parameters on the one hand and the 10 * 2 matrix on the other. The latter is a toy data set and the former is the real data set I ultimately hope to apply this routine to once it works. Also, sorry for not mentioning the fact that the maxBHHH function I am using is from the maxLik package (thanks, Ravi for pointing out). So, the code that is giving me the errors is: maxBHHH(logLikALS4,grad=nuGradientC4,finalHessian=BHHH,start=prm,iterlim=2) and maxBHHH(logLikALS4,grad=nuGradientC4,finalHessian=BHHH,start=prm,iterlim=2) Where nuGradientC4 returns a 2*10 matrix and nuGradientC5 a 10*2 matrix (there are 10 parameters and 2 observations). I have attached the required functions in the .R file. These make for some pretty long code, but all you have to do is either load the file or paste the contents into your R console (and maybe see that they're returning what they're supposed to). I'm sorry I couldn't think of a way to come up with a shorter version of this code (I tried my best). Once you load the file, you should see the following: #The observation level likelihood function logLikALS4(prm) 1 2 -0.6931472 -0.6931472 #The observation level gradients nuGradientC4(prm) 1 2 3 4 5 6 7 8 910 2 -0.3518519 0.3518519 0.000 0 -0.1481481 -0.167 0.1481481 0.167 0.000 0.000 4 0.000 -0.3518519 0.3518519 0 0.000 0.000 -0.167 -0.1481481 0.167 0.1481481 Warning messages: 1: In is.na(x) : is.na() applied to non-(list or vector) of type 'NULL' 2: In is.na(x) : is.na() applied to non-(list or vector) of type 'NULL' nuGradientC5(prm) 2 4 1 -0.3518519 0.000 2 0.3518519 -0.3518519 3 0.000 0.3518519 4 0.000 0.000 5 -0.1481481 0.000 6 -0.167 0.000 7 0.1481481 -0.167 8 0.167 -0.1481481 9 0.000 0.167 10 0.000 0.1481481 Warning messages: 1: In is.na(x) : is.na() applied to non-(list or vector) of type 'NULL' 2: In is.na(x) : is.na() applied to non-(list or vector) of type 'NULL' Ignore the warning messages. The errors are: maxBHHH(logLikALS4,grad=nuGradientC4,finalHessian=BHHH,start=prm,iterlim=2) Error in checkBhhhGrad(g = gr, theta = theta, analytic = (!is.null(attr(f, : the matrix returned by the gradient function (argument 'grad') must have at least as many rows as the number of parameters (10), where each row must correspond to the gradients of the log-likelihood function of an individual (independent) observation: currently, there are (is) 10 parameter(s) but the gradient matrix has only 2 row(s) In addition: Warning messages: 1: In is.na(x) : is.na() applied to non-(list or vector) of type 'NULL' 2: In is.na(x) : is.na() applied to non-(list or vector) of type 'NULL' and: maxBHHH(logLikALS4,grad=nuGradientC5,finalHessian=BHHH,start=prm,iterlim=2) Error in gr[, fixed] - NA : (subscript) logical subscript too long In addition: Warning messages: 1: In is.na(x) : is.na() applied to non-(list or vector) of type 'NULL' 2: In is.na(x) : is.na() applied to non-(list or vector) of type 'NULL' Again, thanks for your patience and help. Rohit On Wed, May 4, 2011 at 4:44 AM, Andrew Robinson a.robin...@ms.unimelb.edu.au wrote: I suggest that you provide some commented, minimal, self-contained, reproducible code. Cheers Andrew On Wed, May 04, 2011 at 02:23:29AM +0530, Rohit Pandey wrote: Hello R community, I have been using R's inbuilt maximum likelihood functions, for the different methods (NR, BFGS, etc). I have figured out how to use all of them except the maxBHHH function. This one is different from the others as it requires an observation level gradient. I am using the following syntax: maxBHHH(logLik,grad=nuGradient,finalHessian=BHHH,start=prm,iterlim=2) where logLik is the likelihood function and returns a vector of observation level likelihoods and nuGradient is a function that returns a matrix with each row corresponding to a single observation and the columns corresponding to the gradient values for each parameter (as is mentioned in the online help). however, this gives me the following error: *Error in checkBhhhGrad(g = gr, theta = theta, analytic = (!is.null(attr(f, : the matrix returned by the gradient function (argument 'grad') must have at least as many rows as the number of parameters (10), where each row must correspond to the gradients of the log-likelihood function of an individual (independent) observation: currently
[R] help with the maxBHHH routine
Hello R community, I have been using R's inbuilt maximum likelihood functions, for the different methods (NR, BFGS, etc). I have figured out how to use all of them except the maxBHHH function. This one is different from the others as it requires an observation level gradient. I am using the following syntax: maxBHHH(logLik,grad=nuGradient,finalHessian=BHHH,start=prm,iterlim=2) where logLik is the likelihood function and returns a vector of observation level likelihoods and nuGradient is a function that returns a matrix with each row corresponding to a single observation and the columns corresponding to the gradient values for each parameter (as is mentioned in the online help). however, this gives me the following error: *Error in checkBhhhGrad(g = gr, theta = theta, analytic = (!is.null(attr(f, : the matrix returned by the gradient function (argument 'grad') must have at least as many rows as the number of parameters (10), where each row must correspond to the gradients of the log-likelihood function of an individual (independent) observation: currently, there are (is) 10 parameter(s) but the gradient matrix has only 2 row(s) * It seems it is expecting as many rows as there are parameters. So, I changed my likelihood function so that it would return the transpose of the earlier matrix (hence returning a matrix with rows equaling parameters and columns, observations). However, when I run the function again, I still get an error: *Error in gr[, fixed] - NA : (subscript) logical subscript too long* I have verified that my gradient function, when summed across observations gives the same results as the in built numerical gradient (to the 11th decimal place - after that, they differ since R's function is numerical). I am trying to run a very large estimation (1000's of observations and 821 parameters) and all of the other methods are taking way too much time (days). This method is our last hope and so, any help will be greatly appreciated. -- Thanks in advance, Rohit Mob: 91 9819926213 [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
[R] Fwd: The results of your email commands
Hi R community, I posted a question on using the R maximum likelihood functions a short while ago and got an email saying that some of the content was unprocessed. Hence, I am reposting the question just to be sure (sorry for the multiple emails if both reached you). My question is reagarding the way we use constraints in programs like maxBFGS, etc. We need to put two matrices into a list, containing the mutipliers on the LHS of the constraint equations and the constants on the RHS. I want to constrain the last parameter of my routine to a negative value. Hence, I specify: lhs=matrix(0,nrow=noOfParameters,ncol=noOfParameters) lhs[noOfParameters,noOfParameters]=-1 rhs=matrix(0,nrow=(noOfParameters)) Then I use: constraints = list(ineqA=lhs,ineqB=rhs) in the maxBFGS function. However, the result is that no matter what parameters I enter (positive, negative or 0), I get an error saying that the initial value is out of bounds. Can you please tell me what I am doing wrong? Thanks in advance, Rohit [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] Questions on dividing lists and tapply
Awesome,that worked! Thanks.
On Wed, Mar 16, 2011 at 6:46 AM, Henrique Dallazuanna www...@gmail.comwrote:
Try this:
mapply('/', l1, l2, SIMPLIFY = FALSE)
and
tapply(1:5, lapply(indxLi, as.numeric), sum)
On Tue, Mar 15, 2011 at 6:06 PM, Rohit Pandey rohitpandey...@gmail.com
wrote:
Hello R community,
I have two questions about using R.
The first is about dividing each element of a list with another similar
sized list. So, if the first list has two elements and so does the
second,
then the result should also be a list with two elements.
For example, the inputs are:
list(matrix(1:6,ncol=2),matrix(1:6,ncol=2))-l1
l2-list(1:3,2)
I want to get a list, l3 with the first element being l1[[1]]/l2[[1]] and
the second one, l1[[2]]/l2[[2]].
I had asked a similar question before and the solution using mapply works
well for a list and a vector, but for two lists, it will return an array
(and not a list).
My second question is about the tapply function.
tapply(1:5,list(c(1,1,2,2,3),c(1,2,1,1,3)),sum)
will give me:
123
1 1 2 NA
2 7 NA NA
3 NA NA 5
The index here is a list: list(c(1,1,2,2,3),c(1,2,1,1,3)).
However, if I get the same index list through one of the other apply
functions (like by) for example,
indxLi-by(rbind(c(1,1,2,2,3),c(1,2,1,1,3)),1:2,function(x){return(x)})
then the tapply no longer works with this list.
tapply(1:5,indxLi,sum) gives me the error:
Error in sort.list(y) : 'x' must be atomic for 'sort.list'
Have you called 'sort' on a list?
Is there a way to use the above list in the tapply function?
Many thanks in advance,
--
Thanks,
Rohit
Mob: 91 9819926213
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide
http://www.R-project.org/posting-guide.htmlhttp://www.r-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
--
Henrique Dallazuanna
Curitiba-Paraná-Brasil
25° 25' 40 S 49° 16' 22 O
--
Thanks,
Rohit
Mob: 91 9819926213
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] Questions on dividing lists and tapply
Hello R community,
I have two questions about using R.
The first is about dividing each element of a list with another similar
sized list. So, if the first list has two elements and so does the second,
then the result should also be a list with two elements.
For example, the inputs are:
list(matrix(1:6,ncol=2),matrix(1:6,ncol=2))-l1
l2-list(1:3,2)
I want to get a list, l3 with the first element being l1[[1]]/l2[[1]] and
the second one, l1[[2]]/l2[[2]].
I had asked a similar question before and the solution using mapply works
well for a list and a vector, but for two lists, it will return an array
(and not a list).
My second question is about the tapply function.
tapply(1:5,list(c(1,1,2,2,3),c(1,2,1,1,3)),sum)
will give me:
123
1 1 2 NA
2 7 NA NA
3 NA NA 5
The index here is a list: list(c(1,1,2,2,3),c(1,2,1,1,3)).
However, if I get the same index list through one of the other apply
functions (like by) for example,
indxLi-by(rbind(c(1,1,2,2,3),c(1,2,1,1,3)),1:2,function(x){return(x)})
then the tapply no longer works with this list.
tapply(1:5,indxLi,sum) gives me the error:
Error in sort.list(y) : 'x' must be atomic for 'sort.list'
Have you called 'sort' on a list?
Is there a way to use the above list in the tapply function?
Many thanks in advance,
--
Thanks,
Rohit
Mob: 91 9819926213
[[alternative HTML version deleted]]
__
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
[R] Mutiplying a data frame to a list
Hi R community, I have a question I'm sure is very simple for most of you. I have a list, with each element being a matrix and the names of the elements are numbers (like 1,3,...). I can extract the matrices and the names individually. Now, I want to multiply each of the names to the individual list matrices (after converting to numbers of course). I could use a for loop, but the very reason I have this list is that I was trying to avoid loops (using lapply). So, turning to one now could defeat the whole purpose. Thanks in advance, -- Thanks, Rohit Mob: 91 9819926213 [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] [Rcpp-devel] Help with integrating R and c/c++
of Dirk Eddelbuettel [ e...@debian.org] Sent: 06 February 2011 18:18 To: Dirk Eddelbuettel Cc: Rohit Pandey; rcpp-devel Subject: Re: [Rcpp-devel] [R] Help with integrating R and c/c++ [ Now resending to rcpp-devel as I had said below I would --Dirk ] On 6 February 2011 at 20:58, Rohit Pandey wrote: | Hi, | | I have been using R for close to two years now and have grown quite | comfortable with the language. I am presently trying to implement an | optimization routine in R (Newton Rhapson). I have some R functions that | calculate the gradient and hessian (pre requisite matrices) fairly | efficiently. Now, I have to call this function iteratively until some | convergance criterion is reached. I think the standard method of doing this | in most programming languages is a while loop. However, I know R can get | pretty slow when you use loops. In order to make this efficient, I want to | transfer this part of my code to a more efficient programming language like | c++ or c. However, I have been trying to learn this all day without any | luck. I found a package called Rcpp that makes this easier. However, it | seems some functional knowledge of writing R packages is a pre requisite. I What gave you that impression? Here is a counter-example, using the packages inline (for cxxfunction) and Rcpp: R library(inline) R src - 'std::cout Hello C++_From_R World std::endl; return(Rcpp::wrap(42));' R rohit - cxxfunction(signature(), src, plugin=Rcpp) R rohit() Hello C++_From_R World [1] 42 R This compiled, linked and loaded a C++ routine built from the two-statement program submitted as character variable. The Rcpp documentation, including its eight vignettes, is full of other examples. Start with Rcpp-introduction and maybe the Rcpp-FAQ. | tried to follow the standard manual for doing this, but could not find a | simple example to get me started. I know I am supposed to make a cpp file | and put it some where before it can be called from R, but I'm confused as to | how this can be done. | | My requirement is to start with a parameter vector, update it according to | the gradient and hessian, check if the parameter satisfies some convergance | criterion and continue doing this until it does. Is there a way to | efficiently do this through an R function (replicate?). The problem is that | the number of iterations is not fixed. If there is no function in R, is | there a way I can quickly use Rcpp or some thing to have this last part of | my code in a C or C++ program which repeatedly calls my R functions for | updating the parameters? Give the example above a first try, and then read some more. The archives of the rcpp-devel (CC'ed; post there for follow-ups after subscribing) list are full of examples, and the CRAN page for Rcpp lists almost two dozen other packages using Rcpp giving you plenty of examples should you want to write a package using Rcpp. Several of these packages do optimization giving you examples of you to pass parameters etc pp. Hope this helps, Dirk | | -- | Thanks in advance, | Rohit | Mob: 91 9819926213 | | [[alternative HTML version deleted]] | | __ | R-help@r-project.org mailing list | https://stat.ethz.ch/mailman/listinfo/r-help | PLEASE do read the posting guide http://www.R-project.org/posting-guide.htmlhttp://www.r-project.org/posting-guide.html | and provide commented, minimal, self-contained, reproducible code. -- Dirk Eddelbuettel | e...@debian.org | http://dirk.eddelbuettel.com ___ Rcpp-devel mailing list rcpp-de...@lists.r-forge.r-project.org https://lists.r-forge.r-project.org/cgi-bin/mailman/listinfo/rcpp-devel -- Thanks, Rohit Mob: 91 9819926213 [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
Re: [R] [Rcpp-devel] Help with integrating R and c/c++
Hi Douglas,
Sorry for leaving that information out earlier.
I am running windows XP. I'm not sure about the tools you mention. I thought
installing the packages in R was enough. Are these tools like a program you
install?
The results of running sessionInfo() are:
R version 2.12.1 (2010-12-16)
Platform: i386-pc-mingw32/i386 (32-bit)
locale:
[1] LC_COLLATE=English_United States.1252 LC_CTYPE=English_United
States.1252LC_MONETARY=English_United States.1252
LC_NUMERIC=C
[5] LC_TIME=English_United States.1252
attached base packages:
[1] stats graphics grDevices utils datasets tcltk methods
base
On Sat, Feb 19, 2011 at 9:21 PM, Douglas Bates ba...@stat.wisc.edu wrote:
On Sat, Feb 19, 2011 at 12:56 AM, Rohit Pandey rohitpandey...@gmail.com
wrote:
Hi Christopher/ Dirk,
Thank you very much for your replys. I think the idea of using inline as
you
suggest is the best way to start off with using c++ with R. I went
through
your examples and also plenty I found on the net. I have been trying to
run
some of these over the past few days, but have consistently been getting
this error message as soon as I run the 'cfunction' or 'cxxfunction'. For
example, in the syntax that Dirk sent,
R library(inline) #Runs perfectly
R src - 'std::cout Hello C++_From_R World std::endl;
return(Rcpp::wrap(42));' #Runs perfectly
R rohit - cxxfunction(signature(), src, plugin=Rcpp)
Now, as soon as I run this line, R spills a whole lot of text out and
gives
an error and a warning:
ERROR(s) during compilation: source code errors or compiler configuration
errors!
Program source:
1:
2: // includes from the plugin
3:
4: #include Rcpp.h
5:
6:
7: #ifndef BEGIN_RCPP
8: #define BEGIN_RCPP
9: #endif
10:
11: #ifndef END_RCPP
12: #define END_RCPP
13: #endif
14:
15: using namespace Rcpp;
16:
17:
18: // user includes
19:
20:
21: // declarations
22: extern C {
23: SEXP file59046688( ) ;
24: }
25:
26: // definition
27:
28: SEXP file59046688( ){
29: BEGIN_RCPP
30: std::cout Hello C++_From_R World std::endl;
return(Rcpp::wrap(42));
31: END_RCPP
32: }
33:
34:
Error in compileCode(f, code, language = language, verbose = verbose) :
Compilation ERROR, function(s)/method(s) not created!
In addition: Warning message:
running command 'C:\PROGRA~1\R\R-212~1.1/bin/i386/R CMD SHLIB
file59046688.cpp 2 file59046688.cpp.err.txt' had status 1
The file59046688.cpp 2 changes every time I run a different function,
but
the problem seems to be the same.
I installed and loaded the inline package (0.3.8) and then the Rcpp
package
(0.9.0). I also tried reversing the order in which I load these, but
still
no luck. I think if I can get just one of these programs to work, I will
be
on my way. Can any of you tell me what I might be doing wrong?
For your question on what exacly I require, Christopher - I just need to
use
a while loop. I have always been able to substitute for loops with some
of
the apply functions in R, but can't seem to be able to replace the while
with a more efficient function. But the things that are required inside
the
while loop, I have already implemented in R efficiently. So, I thought of
transfering just the while loop to a language that is faster with loops.
What operating system and version of R are you using? It would help
if you included the results of executing
sessionInfo()
in R. More importantly, do you have the compiler tools installed and
configured? You need to have certain tools installed on Windows or
Mac OS X before you can compile packages (as opposed to installing
pre-compiled binary packages). Most Linux distributions assume that
their users are adults and provide them with the tools to compile
programs.
Thanks in advance.
On Mon, Feb 7, 2011 at 6:21 AM, Wray, Christopher
christopher.wray...@ucl.ac.uk wrote:
As Dirk says, using inline makes it real simple to start and to
prototype
code.
You mention you have R functions you wish to call via Rcpp. Im not
certain I fully understand what you require here, but it is pretty
simple to
pass R-side functions to C++ via Rcpp, and similarly its simple to send
compiled functions back to R-side as external pointers (and reuse them
elsewhere). Here is a toy example using a simple user function defined
on
the R-side (user_F).
This is evaluated in R, passed as a function parameter to compiled C++
function and evaluated there, and then a compiled version of the
function is
passed back to R as an external pointer, which you can send back to the
C
side and evaluate:
R user_F=function(v){sum((1-v)*exp(-0.5*v))}
cpp - '
NumericVector numvec(xvec);
NumericVector RetVec;
Function userR_f(fun);
List ATR;
typedef SEXP (*h_ptr)(SEXP);
RetVec = userR_f(numvec);
ATR[Fn_ptr]=XPtrh_ptr (new h_ptr(fme));
ATR[Fn_VAL
[R] Help with integrating R and c/c++
Hi, I have been using R for close to two years now and have grown quite comfortable with the language. I am presently trying to implement an optimization routine in R (Newton Rhapson). I have some R functions that calculate the gradient and hessian (pre requisite matrices) fairly efficiently. Now, I have to call this function iteratively until some convergance criterion is reached. I think the standard method of doing this in most programming languages is a while loop. However, I know R can get pretty slow when you use loops. In order to make this efficient, I want to transfer this part of my code to a more efficient programming language like c++ or c. However, I have been trying to learn this all day without any luck. I found a package called Rcpp that makes this easier. However, it seems some functional knowledge of writing R packages is a pre requisite. I tried to follow the standard manual for doing this, but could not find a simple example to get me started. I know I am supposed to make a cpp file and put it some where before it can be called from R, but I'm confused as to how this can be done. My requirement is to start with a parameter vector, update it according to the gradient and hessian, check if the parameter satisfies some convergance criterion and continue doing this until it does. Is there a way to efficiently do this through an R function (replicate?). The problem is that the number of iterations is not fixed. If there is no function in R, is there a way I can quickly use Rcpp or some thing to have this last part of my code in a C or C++ program which repeatedly calls my R functions for updating the parameters? -- Thanks in advance, Rohit Mob: 91 9819926213 [[alternative HTML version deleted]] __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
