search for: nonzeros

Using functions how would I go about do this question? (I already have a mean defined for a function of x.) Write a function called MyMean2. This function has two arguments, x and nonzero, where nonzero has the default value TRUE. This function should return the (Previous defined mean of x) if nonzero=FALSE (Previous defined mean of x) for all x's>0 if nonzero=TRUE Much appreciated.

Hi, I've been trying to figure out a special set of covariance matrices that causes some symmetric zero elements in the inverse covariance matrix but am having trouble figuring out if that is possible. Say, for example, matrix a is a 4x4 covariance matrix with equal variance and zero covariance elements, i.e. [,1] [,2] [,3] [,4] [1,] 4 0 0 0 [2,] 0 4

...t;, count, "\n") cat("Nulls:\n") zeros Here's some code to recreate a file of the same length with nulls in the same places, and spaces everywhere else: size <- count f2 <- tempfile() con <- file(f2, open="wb") count <- 0 while (count < size) { nonzeros <- min(c(size - count, 1000000, zeros - 1)) if (nonzeros) { writeBin(rep(32L, nonzeros), con, size = 1) count <- count + nonzeros } zeros <- zeros - nonzeros if (length(zeros) && min(zeros) == 1) { writeBin(0L, con, size = 1) count <- count + 1...

Can someone verify for me if the for loop below is really calculating the nonzero min for each row of a matrix? I have a bug somewhere in the is section of code. My first guess is how I am find the the nonzero min of each row of my matrix. The overall idea is to make sure I am investing all of my money, i.e. new.set is a set of indicator variables for each stock for a particular portfolio, i.e.

Hi folks, I''ve got most everything done for the pure Ruby version of win32-file. The last thing left (since I''ll be moving the IO methods to a different package eventually) is the file security stuff. Here''s what I''ve got so far for the get_permissions method. However, I''m stuck at GetAce(). If someone could help me finish up this method, I

HI, I would like to extract data in a specific way.  For example, the rainfall data 0,0,1.5,0,0, 3,1,2.5,0,0,0,0, 2.3,0,0,0, 2.1,1.4,0,0,0, 3,2,1,0,0,0... data_1: 1.5, 2.3               ( a single nonzero data between zeros data) data_2: 3.1, 2.5, 2.1,1.4   ( two nonzero data between zeros data) data_3: 3,1,2.5, 3,2,1       ( three nonzero data between zeros data) Thank you so much for any

...) > zeros > > Here's some code to recreate a file of the same length with nulls in the > same places, and spaces everywhere else: > > size <- count > f2 <- tempfile() > con <- file(f2, open="wb") > count <- 0 > while (count < size) { > nonzeros <- min(c(size - count, 1000000, zeros - 1)) > if (nonzeros) { > writeBin(rep(32L, nonzeros), con, size = 1) > count <- count + nonzeros > } > zeros <- zeros - nonzeros > if (length(zeros) && min(zeros) == 1) { > writeBin(0L, con, size = 1) &...

The following example in ?dump.frames options(error = quote({dump.frames(to.file = TRUE); q()})) is useful for teaching the user how to save a frame dump when R encounters an error during non-interactive sessions. This command however causes an additional change that on encountering an error R exits with a 0 error status. Although it's just an example, it's an important one as it's

Hello! I have data containing a large number of probabilities (about 60) of nonzero coefficients to predict 10 different independent variables (in 10 different BMA models). i've arranged these probabilities in a matrix like so: (IV1) (IV2) (IV3) ... p(b0) p(b0) p(b0) p(b1) p(b1) p(b1) p(b2) p(b2) p(b2) ... where p(b1) for independent variable 1 is p(b1 !=

...#39;s some code to recreate a file of the same length with nulls in > the same places, and spaces everywhere else: > > size <- count > f2 <- tempfile() > con <- file(f2, open="wb") > count <- 0 > while (count < size) { > nonzeros <- min(c(size - count, 1000000, zeros - 1)) > if (nonzeros) { > writeBin(rep(32L, nonzeros), con, size = 1) > count <- count + nonzeros > } > zeros <- zeros - nonzeros > if (length(zeros) && min(zeros) == 1) { > w...

hello all, i'm trying to use QPmat, from the popbio package. it appears to be based on solve.QP and is intended for making a population projection matrix. QPmat asks for: nout, A time series of population vectors and C, C constraint matrix, (with two more vectors, b and nonzero). i believe the relevant code from QPmat is: function (nout, C, b, nonzero) { if (!"quadprog" %in%

If this is posted elsewhere I cannot find it. I need to perform multiple integration where some of the variables are in the bounds of the other variables. I was trying to use R2Cuba function but cannot set the upper and lower bounds. My code so far is : int <- function(y){ u2 = y[1] z2 = y[2] u1 =y[3] z1 = y[4] ff <- u1*(z1-u1)*u2*(z2-u2)*exp(-0.027*(12-z2)) return(ff) }

Hi, I'm very new to working with sparse matrices and would like to know how I can column permute a sparse matrix. Here is a small example: > M1 <- > spMatrix(nrow=5,ncol=6,i=sample(5,15,replace=TRUE),j=sample(6,15,replace=TRUE),x=round_any(rnorm(15,2),0.001)) > M1 5 x 6 sparse Matrix of class "dgTMatrix" [1,] 2.983 . 1.656 5.003 . . [2,] .

Full_Name: Chien-yu Peng Version: 2.0.1 OS: Windows XP Professional Submission from: (NULL) (140.109.72.181) Dear all: Although I don't know you, I am thankful for your help. When I use the function mantelhaen.test for R x C x K (R, C > 2) table, the output is not the same as SAS's. I don't know that the result consist with one of SAS's. But it works correctly for 2

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This is useful for probing probing for cache files such as: external_command ?ignore_error:(Some true) ~prog "ls .cache/something.*" will return command output (matched files) on its success or empty list whenits exit code is other than 0 (there are no such files). --- mllib/common_utils.ml | 15 ++++++++++----- mllib/common_utils.mli | 2 +- 2 files changed, 11 insertions(+), 6

Hi, Is there a function func(x) where x is an array such that it returns a list of the indices of all non-zero elements of the array? for example: a: 1 0 0 0 0 1 0 1 0 func(a) returns two vectors r and c: r c 1 1 2 3 3 2 daver +-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+-+ |David Richmond It works on a | + Dept. of Sociology complex scientific

I've only been using R on and off for 9 months and started using the glasso package for sparse covariance estimation. I know the concept is to shrink some of the elements of the covariance matrix to zero. However, say I have a dataset that I know has some underlying "baseline" covariance/correlation (say, a value of 0.3), how can I change or incorporate that into to the

hi ?integer says: Note that on almost all implementations of R the range of representable integers is restricted to about +/-2*10^9: 'double's can hold much larger integers exactly. I am getting very confused as to when to use integers and when not to. In my line I need exact comparisons of large integer-valued arrays, so I often use as.integer(), but the above

Dear all, I have a task to find the first all zero row of a matrix X ( nothing known about X). I need to write a function which returns either the row index of the first all-zero row, or NA if there are no all-zero rows. and I also need to locate all rows which are non-zero (should be a vector of row indexes). Can somebody give me some hints on this? Thanks a lot. Rene. [[alternative HTML