similar to: don't print object attributes on screen

Dear Helpers, I wrote a simple function to standardise variables if they contain more than one value. If the elements of the variable are all identical, then I want the function to return zero. When I submit variables whose elements are all identical to the function, it returns not zero, but NaNs. zt=function(x){if (length(table(x)>1)) y=(x-mean(x))/sd(x) else if (length(table(x)==1)) y=0;

Dear Helpers, I wrote a simple function to standardise variables if they contain more than one value. If the elements of the variable are all identical, then I want the function to return zero. When I submit variables whose elements are all identical to the function, it returns not zero, but NaNs. zt=function(x){if (length(table(x)>1)) y=(x-mean(x))/sd(x) else if (length(table(x)==1)) y=0;

Moi! A student here has been getting a bit irritated with some side effects of scale() (OS is Windows XP, the behaviour occurs in R 2.0.0, but not 1.7.1). The problem is that she scales a variable in a data frame, then does a regression, and tries to get some predictions for some new data. However, at this point she gets an error (see the example below). This seems to be because the

Dear all; This must have a rather simple answer but haven't been able to figure it out: I have a data frame with say 2 groups (group 1 & 2). I want to select from group 1 say "n" rows and calculate the mean; then select "m" rows from group 2 and calculate the mean as well. So far I've been using a for loop for doing it but when it comes to a large data set is

Dear all; Is there any way to make this to work?: .x<-rnorm(50,10,3) .y<-.x+rnorm(50,0,1) X<-data.frame(.x,.y) colnames(X)<-c("Xvar","Yvar") Ytext<-"Yvar" lm(Ytext~Xvar,data=X) # doesn't run lm(Yvar~Xvar,data=X) # does run The main idea is to use Ytext as input in a function, so you just type "Yvar" and the model should fit....

Here are several ways to get there, but your original loop is fine once it is corrected: > for (i in 1:2) smean[i] <- mean(toy$diam[toy$group==i][1:nsel[i]]) > smean [1] 0.271489 1.117015 Using sapply() to hide the loop: > smean <- sapply(1:2, function(x) mean((toy$diam[toy$group==x])[1:nsel[x]])) > smean [1] 0.271489 1.117015 Or use head() > smean <- sapply(1:2,

Hi Pedro, This may not be much of an improvement, but it was a challenge. selvec<-as.vector(matrix(c(nsel,unlist(by(toy$diam,toy$group,length))-nsel), ncol=2,byrow=TRUE)) TFvec<-rep(c(TRUE,FALSE),length.out=length(selvec)) toynsel<-rep(TFvec,selvec) by(toy[toynsel,]$diam,toy[toynsel,]$group,mean) Jim On 4/3/16, Pedro Mardones <mardones.p at gmail.com> wrote: > Dear all; >

Dear R users; Is it possible to get the row and column number of a particular entry in a dist object? Let's say that I want to find the position of the value 1.1837 (the last entry on the dist object below), that is [6,3]. Can I get those values without transforming the object to a matrix?, i.e. working with the dist object only. 1 2 3 2 0.23935864

Dear all; A very basic question. I have the following data: ************************************************************************************ A <- 1/1000*c(347,328,129,122,18,57,105,188,57,257,53,108,336,163, 62,112,334,249,45,244,211,175,174,26,375,346,153,32, 89,32,358,202,123,131,88,36,30,67,96,135,219,122, 89,117,86,169,179,54,48,40,54,568,664,277,91,290,

Dear all; Does anyone know how to add grid lines to a persp plot? I've tried using lines(trans3d..) but the lines of course are superimposed into the actual 3d surface and what I need is something like the plot shown in the following link: http://thermal.gg.utah.edu/tutorials/matlab/matlab_tutorial.html I'll appreciate any ideas Thanks PM

Hi all; I'm trying to display a 2 panel plot for the Puromycin data from R with 2 different non-linear models fitted to each group. The problem is that as far as I know panel.number doesn't work in the latest version of R. Can anyone give a hint how to solve this? Here is the code that I used before and now doesn't work xyplot(rate ~conc| state,Puromycin,

Dear all; What can be wrong with this simple example? library(boot) d1<-c(rnorm(10,mean=10)) fm<-function(d,i) mean(d[i]) bd1<-boot(d1,fm,10000) > Error: evaluation nested too deeply: infinite recursion / options(expressions=)? Thanks for any idea

Dear R users; Consider the following toy example: a <- matrix(c(2,3,4,NA,NA,5,8,NA,8,NA), 5, 2) b <- cbind(a,apply(a, 1, diff, na.rm = TRUE)) What I would like be able to get is: c <- matrix(c(2,3,4,NA,NA,5,8,NA,8,NA,3,5,-4,8,NA), 5, 3) i.e., for each row if both values (column 1 and 2) are NA then the difference must return NA, but if any of those two values is different from NA

Dear all; I'm wondering if there is any 'efficient' approach for selecting a sample of 'every nth rows' from a dataframe. For example, let's use the dataframe GAGurine in MASS library: > length(GAGurine[,1]) [1] 314 # select an 75% of the dataset, i.e. = 236 rows, every 2 rows starting from row 1 > test<-GAGurine[seq(1,314,2),] > length(test[,1]) [1] 157 #

Dear all; I'm trying to create a 2 x 3 plot (something I know like lattice can do better) using the plot function. However; I'm not sure how to make the width of the plots to be the same on each column. I guess the answer maybe obvious but I haven't been able to figure it out. I'll appreciate any suggestion. Here is the (highly inefficient) code for the first row: par(mfrow =

I would like to try to implement a big series of nested loops in a C code and then call it from R; however I'm not familiar with C programming. Does anyone know about some sort of reference I can use that help me to translate my code to C? (I'm thinking on something like to Octave to R reference posted in CRAN) thanks PM

Dear all; I have a data set with 3 groups and 2 response variables, say z1 and z2, and I would like to create a single plot (using the levelplot function) showing on the first row the leveplots for z1 for each group and on the second row levelplots for z2 for the same groups. I tried plot.trellis using the split option and it's OK but what I would like to achieve is something similar to what

Does anyone can provide a code to implement least median squares regression in R (not using the lqs function or calling C functions)? Reason: teaching/learning purposes Thanks PM

Dear R-users; I'm working with a a dataset that was previously used to fit a nonlinear model of the form: Y ~ a * (1 + b * log(1 - c * X^d)) The parameters published elsewhere are: a = 1.758863, b = .217217, c = .99031, and d = .054589 However, there is no way I can replicate this result. I've tried several options (including SAS) w/o success. The data is: X <-

Toda la razon!!! merge era todo! Saludos El mié., 20 mar. 2019 a las 10:57, Carlos Ortega (<cof en qualityexcellence.es>) escribió: > Hola Mauricio, > > No, creo que no es lo que dices.. > > Con merge, indicas por qué columna (pueden ser varias) quieres juntar los > dos dataframes y con los parámetros "all.x", "all.y" y "all" indicas si