similar to: FW: subset using noncontiguous variables by name (not index)

Hi All, I'm using the subset function to select a list of variables, some of which are contiguous in the data frame, and others of which are not. It works fine when I use the form: subset(mydata,select=c(x1,x3:x5,x7) ) In reality, my list is far more complex. So I would like to store it in a variable to substitute in for c(x1,x3:x5,x7) but cannot get it to work. That use of the c function

I am relatively new to R and object oriented programming. I have relied on SAS for most of my data analysis. I teach an introductory undergraduate forecasting course using the Diebold text and I am considering using R in addition to SAS and Eviews in the course. I work primarily with univariate or multivariate time series data. I am having a great deal of difficulty understanding and working with

Dear all I have a work-flow issue with lm(). When I use > lm(y1~x1, anscombe) Call: lm(formula = y1 ~ x1, data = anscombe) Coefficients: (Intercept) x1 3.0001 0.5001 I get as expected the formula, "y1 ~ x1", in the print()ed results or summary(). However, if I pass through a formula object > (form <- formula(y1~x1)) y1 ~ x1 > lm(form, anscombe) Call:

Dear R Group Here is what i am trying to do.. but couldnt figure out how.. string<-"ABC DEFG HIJKLM NOPQ RSTUV WXY" string1<-substr(string,1,4) I want to create an R object string 2 ( following the logic shown).. R does not allow string subtraction.. any suggestions how to achieve this? string2<-string-string1 (it should now hold "DEFG HIJKLM NOPQ RSTUV WXY" I

I have a question about the D'Agostino skewness test and the Anscombe-Glynn kurtosis test. agostino.test(x, alternative = c("two.sided", "less", "greater")) anscombe.test(x, alternative = c("two.sided", "less", "greater")) The option "alternative" in those two functions seems to be the null hypothesis. In the output, the

Another bad case is > moments::anscombe.test(rep(c(1,1.1),length=35)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed I haven't checked the formulas carefully, but I suspect the problem is from taking the cube root of a negative number in z <- (1 - 2/(9 * a) - ((1 - 2/a)/(1 + xx * sqrt(2/(a - 4))))^(1/3))/sqrt(2/(9 * a)) In R, the

This is 100% functionally equivalent to 3.54-pre1, with only a few minor documentation changes. Changes in 3.54: * Add "menu separator", "menu indent", "menu disabled" (see README.menu). * vesamenu: fix handing of VESA modes with noncontiguous memory buffers. In particular, Qemu/KVM sets up such a mode when Cirrus

moments::anscombe.test(x) does give errors when x has too few values or if all the values in x are the same > moments::anscombe.test(c(1,2,6)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed > moments::anscombe.test(c(2,2,2,2,2,2,2,2)) Error in if (pval > 1) pval <- 2 - pval : missing value where TRUE/FALSE needed You can use tryCatch() to

Hi Bill, Thanks for prompt reply and letting me know a way around it. I have more than 1200 observations and not all the values are the same. However, my data points are quite similar, for example, 0.079275, 0.078867, 0.070716 in millions and etc. I have run the data without converting it to millions and I still get the same error message. As I have kurtosis value, it should be fine for the

Hi all, I'm extracting the name of the term in a regression model that dropterm specifies as the least significant one, and I'm assigning this name to an object. However, when I use update(), it ignores this object. Is there a way I can make it not ignore it? A reproducible example is below: > lm(x1~1+y1*y2+y3+y4,data=anscombe)->my.lm >

Dear useRs, I was searching CRAN for implementation of kurtosis and skewness tests, and found that there is some kind of lack on it. So, I have written three functions: 1. Anscombe-Glynn test for kurtosis 2. Bonett-Seier test based on Geary's kurtosis (which is not widely known, but I was inspired by original paper describing it, found coincidentally in Elsevier database) 3.

Hi, I have the following problem. It has two parts. 1. I need to calculate the stationary probabilities of a Markov chain, eg if the transition matrix is P, I need x such that xP = x in other words, the left eigenvectors of P which have an eigenvalue of one. Currently I am using eigen(t(P)) and then pick out the vectors I need. However, this seems to be an overkill (I only need a single

Hi all, Running simulations, I'm generating market response to 2 factors X&Y.. There is no closed form for the market response.. The results are store in a matrix Z(X <- seq(.02,.98,.02), Y <- seq(.01,.19,.01)).. For optmization purpose I need to approximate the values for any factor X in 0,02-0,98 and Y in 0,01-0,19 How can I do it ? For one factor : Xn-1 < x <= Xn

What is going on here? In the lines ending in #### the inputs and outputs are identical yet one gives a warning and the other does not. a1 <- `rownames<-`(anscombe[1:3, ], NULL) a2 <- anscombe[1:3, ] ix <- 5:8 # input arguments to #### are identical in both cases identical(stack(a1[ix]), stack(a2[ix])) ## [1] TRUE identical(a1[-ix], a2[-ix]) ## [1] TRUE res1 <-

They differ in whether the row names are "automatic": > .row_names_info(a1) [1] -3 > .row_names_info(a2) [1] 3 Best, -Deepayan On Tue, 14 Nov 2023 at 08:23, Gabor Grothendieck <ggrothendieck at gmail.com> wrote: > > What is going on here? In the lines ending in #### the inputs and outputs > are identical yet one gives a warning and the other does not. > >

Dear R-users, I am comparing differences in variance, skew, and kurtosis between two groups. For variance the comparison is easy: just var.test(group1, group2) I am using agostino.test() for skew, and anscombe.test() for kurtosis. However, I can't find an equivalent of the F.test or Mood.test for comparing kurtosis or skewness between two samples. Would the test just be a 1 df test on

Hi to all, how could I to rotate automatically a data sheet which was imported by read.xls? x1 x2 x3 .... xn y1 1 4 7 ... xn/y1 y2 2 5 8 .... xn/y2 y3 3 6 9 ....xn/y2 yn ... ... ... Xn/Yn to y1 y2 y3 .... yn x1 1 2 3 ..... Yn/x1 x2 4 5 6 .... Yn/x2 x3 7 8 9 .... Yn/x2 xn ... ... ... ..... Yn/xn Kind regards Knut

In that case identical should be FALSE but it is TRUE identical(a1, a2) ## [1] TRUE On Tue, Nov 14, 2023 at 8:58?AM Deepayan Sarkar <deepayan.sarkar at gmail.com> wrote: > > They differ in whether the row names are "automatic": > > > .row_names_info(a1) > [1] -3 > > .row_names_info(a2) > [1] 3 > > Best, > -Deepayan > > On Tue, 14 Nov

Hi list, Does samba support IDN (Internationalized domain name) ? I created a domain in windows server 2008 (function level 2003) and domain name is "TEST???.COM <http://xn--test-ooa2iub.COM>". I want to join domain as a member. When I run "kinit administrator at TEST???.COM" after setting krb5.conf, kinit failed. kinit administrator at TEST???.COM Conversion error:

Can someone offer some advice on how to properly evaluate a SYMSXP from a .Call ? I have the following in R: variable xn, with an attribute "mu" which references the variable mu in the global environment. I know "references" is a loose term; mu was defined in this fashion as a way to implement deferred binding: foo <- function(x,mu) { attr(x,"mu") <-