similar to: Help with Functions

Hi wizards, I have seen the function svd of R for singular value decomposition, but I need to computes the ``economy size'' or ``thin'' singular value decomposition of a matrix in R. Somebody knows how to do that?. Thanks in advance. -- Web Page http://geocities.com/lord_tyranus_96/

Hi list, I am writing several functions and running out variable names. I am using words such as "t", "c", "matrix" to keep the notation same as formulas I am using. For example I have, unnormalized <- function(t, x, y){ val <- rnorm(t, mean=x, var=y) return(val) } metropolis <- function(t, c, x, y){ den1 <- unnormalized(t, mean=x, sd=y)

Hi Duncan et al, Our linker guy brought up a problem with how we pad out our exception tables. Right now we pad them out like this: .section __DATA,__gcc_except_tab .align 2 GCC_except_table13: .byte 0x0 #< --- hun? .byte 0x0 #< --- hun? Lexception13: .byte 0xFF .byte 0x0 .byte 0xB2, 0x1 > Here are his comments: The problem is that the linker parses FDE which gives it

Hi Bill, > It looks like your goal is to keep the 32-bit pointers in the call-site table 4-byte aligned. Here is another solution, instead of having two labels at the start of the LSDA (with pad bytes between them), have no pad bytes and instead use an unnormalized uleb128 for the call-site table length. By unnormalized, I mean one with leading zeros. For instance, instead of: this sounds

I am adding -D k=v to yaml2obj, similar to clang -D. This makes it easy to generate {32-bit,64-bit} x {big-endian,little-endian} tests. --- !ELF FileHeader: Class: ELFCLASS[[BITS]] Data: ELFDATA2[[ENCODE]] Type: ET_DYN Machine: EM_X86_64 # RUN: yaml2obj -D BITS=32 -D ENCODE=LSB %s -o %t.32le # RUN: yaml2obj -D BITS=32 -D ENCODE=MSB %s -o %t.32le # RUN: yaml2obj

>> It looks like your goal is to keep the 32-bit pointers in the call-site table 4-byte aligned. Here is another solution, instead of having two labels at the start of the LSDA (with pad bytes between them), have no pad bytes and instead use an unnormalized uleb128 for the call-site table length. By unnormalized, I mean one with leading zeros. For instance, instead of: > > this sounds

On Feb 5, 2010, at 4:00 PM, Duncan Sands wrote: > Hi Bill, > >> It looks like your goal is to keep the 32-bit pointers in the call-site table 4-byte aligned. Here is another solution, instead of having two labels at the start of the LSDA (with pad bytes between them), have no pad bytes and instead use an unnormalized uleb128 for the call-site table length. By unnormalized, I mean one

I have hit a problem with the design of the mcmc package I can't figure out, possibly because I don't really understand the R function call mechanism. The function metrop in the mcmc package has a ... argument that it passes to one or two user-supplied functions, which are other arguments to metrop. When the two functions don't have the same arguments, this doesn't work.

How can I get the result of, e.g., poly(1:3. degree=2) to give me the unnormalized integer coefficients usually used to explain orthogonal polynomial contrasts, e.g, -1 1 0 -2 1 1 As I understand things, the columns of x^{1:degree} are first centered and then are normalized by 1/sqrt(col sum of squares), but I can't see how to relate this to what is returned by poly(). >

I'm trying to use a lattice function within a function and have problems passing the "groups" argument properly. Let's say I have a data frame d <- data.frame(x = rnorm(100), y = c("a", "b")) and want to plot variable x in a densityplot, grouped by the variable y, then I would do something like densityplot(~ x, d, groups = y) If however I wanted to

?The idea itself is indeed good. Regarding to escaping: I think we should have it. Imagine the following example (I've took it from D73828). --- !ELF FileHeader: Class: ELFCLASS[[BITS]] Data: ELFDATA2LSB Type: ET_EXEC Machine: EM_386 # RUN: yaml2obj %s --docnum=4 -D BITS=32 -o %t-32bit.o # RUN: yaml2obj %s --docnum=4 -D BITS=64 -o %t-64bit.o Without escaping it would

Dear Prof Ripley, First of all, unless you are an english professor, then I do not think you have any business policing language. I'm still very much a student, both in R, and regarding signal analysis. My competence on the subject as compared too your own level of expertise, or my spelling for that matter, may be a contension for you, but it would have been better had you kept that opinion

Hi I am looking for an implementation (or alternative to) Mallow's distance or the Earth Mover's distance to compare distributions or unnormalized distributions (signatures). Is there an implementation in R or can somebody recommend an alternative? Thanks Rainer -- Rainer M. Krug, PhD (Conservation Ecology, SUN), MSc (Conservation Biology, UCT), Dipl. Phys. (Germany) Centre of

Dear R users, if all my numerical variables in my datasets having the same units, may I leave them unnormalized, just do cv.glmnet directly(cv.glmnet(data,standardize=FALSE))? i know normally if there is a mixture of numerical and categorical , one has to standardize the numerical part before applying cv.glmnet with standardize=fase, but that's due to the different units in the numerical

*Hi all,* * * *The following is my general idea for the project. For a complete query parser I still need to consider more details. Please give me feedback because the description of this project is lack of detailed information, and I can submit my proposal without giant deviation.* * * design principle of query parsing: 1) better understanding user input. All search engine do is understanding

Dear all, Can any one tell me how can i perform Orthogonal Polynomial Regression parameter estimation in R? -------------------------------------------- Here is an "Orthogonal Polynomial" Regression problem collected from Draper, Smith(1981), page 269. Note that only value of alpha0 (intercept term) and signs of each estimate match with the result obtained from coef(orth.fit). What

Hi, I try to calculate the angle between two first eigenvectors of different covariance matrices of biological phenotypic traits for different populations. My issue here is, that all possibilities to do so seem to normalize the eigenvectors to length 1. Although the helpfile of eigen() states, that using eigen(, symmetric = FALSE, EISPACK =TRUE) skips normalization this is (I guess) not applicable

Hi list, I'm looking about lda function. I'd like to know how calcolate the value of the discriminant functions for the original datas. I see that in the result object "lda" there is $scaling a matrix which transforms observations to discriminant functions, normalized so that within groups covariance matrix is spherical. I'd like to have the value of the discriminant

Hi all, Thank you for giving me the opportunity to work with Xapian :) I am Jiarong Wei, a third year undergraduate student in Zhejiang University, China. In GSoC 2014, I will work on Letor module with Hanxiao Sun. Here are some questions I encountered these days, 1. In letor.cc, we have two parts of functions: the training part and the ranking part. I?ll use SVMRanker as an example. The

hello, i am currently using acts_as_ferret in one of my applications and now would like to also incorproate tags. i came across somesones blog that had this: ////// Having Ferret index method results (like :tag_list) worked out-of-the-box for me with acts_as_ferret. I specified attributes (table columns) as strings and methods as symbols, like so: acts_as_ferret :fields => [?title?,