similar to: NaN behavior of cumsum

Hi, I'm currently in the process of writing an R-installation SOP for my company. As part of that process I'm using the recommendations from the 'R Installation and Administration' document, section 3.2, "Testing an installation". This is done on an XP machine, using the latest binary of 2.11.0. The binary is downloaded and then installed from the installer. I then

Dear all, in R 3.1.0, this is happening: > cummin(c(1+1i,2-3i,4+5i)) Error in cummin(c(1 + (0+1i), 2 - (0+3i), 4 + (0+5i))) : 'cummax' not defined for complex numbers > cummax(c(1+1i,2-3i,4+5i)) Error in cummax(c(1 + (0+1i), 2 - (0+3i), 4 + (0+5i))) : 'cummin' not defined for complex numbers It may be fixed in R-devel, but I thought I'd mention it to make sure

Hi, The function cummax() seems to have a bug. > x <- c(NA, 0) > storage.mode(x) <- "integer" > cummax(x) [1] NA 0 The correct result of this case should be NA NA. The mistake in [ https://github.com/wch/r-source/blob/trunk/src/main/cum.c#L130-L136] may be the reason. Best Regards, Dongcan -- Dongcan Jiang Team of Search Engine & Web Mining School of Electronic

Hi, I have two questions want to ask. 1. If I have a matrix like this, and I want to figure out the rows whose value in the 3rd column are less than 0.05. How can I do it with R. hsa-let-7a--MBTD1 0.528239197 2.41E-05 hsa-let-7a--APOBEC1 0.507869409 5.51E-05 hsa-let-7a--PAPOLA 0.470451884 0.000221774 hsa-let-7a--NF2 0.469280186 0.000231065 hsa-let-7a--SLC17A5

Hello, I'm dealing with financial time series. I'm trying to find out X in this sentence: The most recent close is the lowest level since X(date). Here's an example of what I'm looking for: library(fBasics) data(DowJones30) tail(DowJones30[,1:5],n=10) I need to come up with a vector that would look like this AA AXP T ... 2000-12-21

Dear useRs, a new and much improved version of the zoo package for indexed totally ordered observations (such as irregular time series) is available from CRAN. It allows indexing observations with time/index vectors of arbitrary class and extends many of the standard generic functions also available for "ts" objects. Additionally, it allows conversion from/to other (irregular) time

Dear useRs, a new and much improved version of the zoo package for indexed totally ordered observations (such as irregular time series) is available from CRAN. It allows indexing observations with time/index vectors of arbitrary class and extends many of the standard generic functions also available for "ts" objects. Additionally, it allows conversion from/to other (irregular) time

Hello, I am searching for a function to calculate "partial" cumsums. For example it should calculate the cumulative sums until a NA appears, and restart the cumsum calculation after the NA. this: x <- c(1, 2, 3, NA, 5, 6, 7, 8, 9, 10) should become this: 1 3 6 NA 5 11 18 26 35 45 any ideas? thank you and best regards, stefan

Hi, I am running R 2.13.0 on a Windows 7 machine. I ran the script: testInstalledBasic('devel') and received the following warning message: running tests of consistency of as/is.* creating ?isas-tests.R? running code in ?isas-tests.R? comparing ?isas-tests.Rout? to ?isas-tests.Rout.save? ...running tests of random deviate generation -- fails occasionally running code in

Is there anything like cumsum and cumprod but which allows you to apply an arbitrary function instead of sum and product? In other words, I want a function cumfunc(x, f) that returns a vector, so that for all n up to the length of x cumapply(x,f)[n] = f(x[1:n]) This would give cumsum and cumprod as special cases when f=sum or f=prod. I could write such a function, but I can't see

R-2.9.0/include/R_ext/Arith.h has: int R_IsNA(double); /* True for R's NA only */ int R_IsNaN(double); /* True for special NaN, *not* for NA */ int R_finite(double); /* True if none of NA, NaN, +/-Inf */ #define ISNA(x) R_IsNA(x) /* True for *both* NA and NaN. The first and last lines are contradictory - if R_IsNA is true only for NA, not NaN, then ISNA should be the same.

I spent a lot of time searching and came up empty handed on the following query. Is there an equivalent to rowSums that does product or cumulative product and avoids use of apply or looping? I found a rowProd in a package but it was a convenience function for apply. As part of a likelihood calculation called from optim, I?m computing products and cumulative products of rows of matrices with

Hello R-devel, Best wishes in the new year. I am writing to kindly request new R function so NA_real_ can be more easily detected. Currently if one wants to test for NA_real_ (but not NaN) then extra work has to be done: `is.na(x) & !is.nan(x)` Required functionality is already at C level so to address my request there is not that much to do. Kevin Ushey made a nice summary of current R C api

Dear R-help, I have been trying really hard to generate the following vector given the data (x) and parameter (alpha) efficiently. Let y be the output list, the aim is to produce the the following vector(y) with at least half the time used by the loop example below. y[1] = alpha * x[1] y[2] = alpha^2 * x[1] + alpha * x[2] y[3] = alpha^3 * x[1] + alpha^2 * x[2] + alpha * x[3] ..... below are

Full_Name: J. Sisk Version: 1.6.1 OS: Linux (RedHat 8) Submission from: (NULL) (67.119.41.66) Suppose you make a data-frame like so: xxx <- data.frame(a=10,b=20,c=30,d=40) Then cumprod(xxx[1,]) returns > cumprod(xxx[1,]) a b c d 1 10 20 30 40 The documentation for cumprod says that it should work on "numerical objects", and this is a data-frame, but it

I append below a suggested update for p.adjust(). 1. A new method "yh" for control of FDR is included which is valid for any dependency structure. Reference is Benjamini, Y., and Yekutieli, D. (2001). The control of the false discovery rate in multiple testing under dependency. Annals of Statistics 29, 1165-1188. 2. I've re-named the "fdr" method to "bh" but

I've noticed that the max.col function with the default "random" option often gives unexpected results. For instance, in this test, it seems clear what the answer should be: > # second col should always be max > x1 = cbind(1:10, 2:11, -Inf) > > # this works fine > max.col(x1, "first") [1] 2 2 2 2 2 2 2 2 2 2 > > # this gives random answers >

Hi. Suppose I have a vector that I partition into disjoint, contiguous subvectors. For example, let v = c(1,4,2,6,7,5), partition it into three subvectors, v1 = v[1:3], v2 = v[4], v3 = v[5:6]. I want to find the maximum element of each subvector. In this example, max(v1) is 4, max(v2) is 6, max(v3) is 7. If I knew that the successive subvector maxima would never decrease, as in the example,

Hi! I was wondering about the behavior of the range function wrt. logical NAs: > range(c(0L, 1L, NA), finite=T) [1] 0 1 > range(c(F, T, NA), finite=T) [1] NA NA The documentation is quite clear that "finite = TRUE includes na.rm = TRUE?, so that I would have assumed that these two snippets would produce the same result. - Lukas

"nana" is meant to express "NA, really NA". Your suggestion sounds good. On Thu 2 Jan, 2020, 3:38 AM Pages, Herve, <hpages at fredhutch.org> wrote: > Happy New Year everybody! > > The name (is.nana) doesn't make much sense to me. Can you explain it? > > One alternative would be to add an extra argument (e.g. 'strict') to > is.na(). FALSE by