similar to: using eval to handle column names in function calling scatterplot graph function

I compiled and tried rsync 2.5.0 but could not get the server running. loadparm.c:string_set() now calls free() which it did not do in 2.4.6 and this free() tries to free memory that was not allocated with malloc. Here is a gdb run (done after adding return before fork() in become_daemon) which shows where it crashes and what my minimal config file for demonstrating the bug was. The config file

When reshaping a dataframe in which there are unused factor levels in the id variable, I get the following error: Error in if (!all(really.constant)) warning(gettextf("some constant variables (%s) are really varying", : missing value where TRUE/FALSE needed For example, > df <- data.frame(i = factor(rep(1:5, each = 2)), t = factor(rep(1:2, 5)), x = rep(rbinom(5, 1,

Hi, I have a data frame df with column names a,b and c. Now I want to get a subset of df that satified the condition a == 1 and b == 2, how do I specify this. For one condition like a == 1 I can use subdf = df[,df$a==1] to get the right answer, but subdf = df[,df$a==1 && df$b ==2] does not return the right answer. Some quick tips please.

I've been working on a new package and I have a few questions regarding the behaviour of the nlm function. I've been (for better or worse) using the nlm function to fit a linear model without suppling the hessian or gradient attributes in the objective function. I'm curious as to why the nlm requires 31 iterations (for the linear model), and then it doesn't work when I try to add

I have a large dataset similar to this: ID time result A 1 5 A 2 2 A 3 1 A 4 1 A 5 1 A 6 2 A 7 3 A 8 4 B 1 3 B 2 2 B 3 4 B 4 6 B 5 8 I need to extract a number of features for each individual in it (identified by "ID"). These are: * The lowest result (the nadir) * The time of the nadir - but if the nadir level is present at >1 time point, I need the minimum and maximum time of nadir

Hello R users, This is more of a convenience question that I hope others might find useful if there is a better answer. I work with large datasets that requires multiple parsing stages for different analysis. For example, compare group 3 vs. group 4. A more complicated comparison would be time B in group 3 of group L with B in group 4 of group L. I normally subset each group with the

Hello folks, I have a big project to work on and the dataset is classified so I am just going to use my own example so everyone can understand what I am targeting. Let's take Target as an example: We consider three brands of tape: Target brand, 3M and Avery. The original data frame has 4 columns: Year of Record, Product_Name(which contains three brands of tape), Sales, and Region. I want to

Hello, I want to solve a nonlinear 3SLS problem with "nlsystemfit()". The equations are of the form y_it = f_i(x,t,theta) The functions f_i(.) have to be formulated as R-functions. When invoking "nlsystemfit()" I get the error Error in deriv.formula(eqns[[i]], names(parmnames)) : Function 'f1' is not in the derivatives table

Hi Again, First of all thank you for all the responses to my previous query. Your answers were very helpful and I did the job ;-). Now I hope you can answer as quick the following (sorry I am invading you with trivial questions): Let?s use again the following data.frame example: DF <- data.frame(x=rnorm(5), y=rnorm(5)) I want to obtain a new data.frame (or matrix) that contains only n

Hi, the section "Global Parameters" of the current http://rsync.samba.org/ftp/rsync/rsyncd.conf.html says: "You may use references to environment variables in the values of parameters. String parameters will have %VAR% references expanded as late as possible (when the string is used in the program), allowing for the use of variables that rsync sets at connection time, such as

Hi all, I've been using the scatterplot3d function (from the scatterplot3d library) to create 3D plots. I was wondering whether there is anyway to group the points according to a particular group variable. For example I used the plot function as plot( factor( <GROUPINGVAR> ) , <PLOTVARS> ) to organise the results in a according to the grouping variable. I was wondering

Hello, I would like to perform a Partial least square discriminate analysis (PLSDA) in R. To do this I use the package mixOmics. I could perform the PLSDA in R. however I would also like to perform a leave-one-out cross validation in order to assess the performance of my model. My supervisor told me that I should focus on the R2/Q2 ratios. However when I read the instruction for running the