similar to: Create a function with multiple object as an output

Hello, I'm having two similar problems with for loop and I would appreciate any help or comment. I want to use "for loop" to calculate series of initial values for an optimization problem. But some initial values have my function quit due to problems like calculating the inverse of singular matrices. I don't want to make my program check determinants and skip it if it is

Hello R-devel, I would like to suggest a couple of updates for the R FAQ. https://CRAN.R-project.org/bin/linux/suse is currently empty and the directory has mtime from 2012, so it probably doesn't help to reference it in FAQ 2.6. There seems to be increased interest in using variables as variable names [1,2], so it might be useful to expand 7.21 a little. Can an R FAQ entry link to R-intro

Dear Group, I am having a function that I am running in a loop that generated two results for each loop The result1 is a zoo object The result2 is a data frame Now I want to put both of them in a list or some structure ... that I can access or output to a file after the loop is done. For e.g. for (i in 1:20){ niceFunction(x[i],i) } niceFunction (x,i) { result1 = someOperations() #zoo

Hopefully an easy one, how do I merge two or more SQL query results? Example: result1 = find_by_sql(x) result2 = find_by_sql(y) What is the best way to merge result1 and result2? I want to be able to reference the objects as if they were obtained via one query. Cheers, Dan

I have written the R code below to perform White's Data Mining Reality Check (DMRC) but as it stands at the moment it is painfully slow. It is written as a function as I call it many times from a script file with different data input, and the output is sunk() to a text file. Could anyone suggest improvements to the code to increase its speed? boot_white_test <- function(data) {

Dear List, Shouldn't result1 and result2 be equal in the following case? Note that log$RequestID is a factor. That is, is.factor(log$RequestID) yields TRUE. result1 <- tapply(log$Flag,factor(log$RequestID),sum) result2 <- tapply(log$Flag,log$RequestID,sum) Yet, when I summarize the output, I get the following: summary(result1) Min. 1st Qu. Median Mean 3rd Qu.

On Sep 24, 2013, at 4:07 PM, Sean Silva <chisophugis at gmail.com> wrote: > On Tue, Sep 24, 2013 at 4:17 PM, Nick Kledzik <kledzik at apple.com> wrote: > > On Sep 24, 2013, at 12:40 PM, Michael Spencer <bigcheesegs at gmail.com> wrote: > >> On Tue, Sep 24, 2013 at 12:33 PM, Rui Ueyama <ruiu at google.com> wrote: >> Hi LLD developers, >>

On Tue, Sep 24, 2013 at 4:17 PM, Nick Kledzik <kledzik at apple.com> wrote: > > On Sep 24, 2013, at 12:40 PM, Michael Spencer <bigcheesegs at gmail.com> > wrote: > > On Tue, Sep 24, 2013 at 12:33 PM, Rui Ueyama <ruiu at google.com> wrote: > >> Hi LLD developers, >> >> I'm about to make a change to invert the return value of Driver::parse()

I''ve just found myself stuck trying to rspec something so am hoping someone more knowledgable can help. I have a Connector class which has a class method ''results'' that yields results it get from a network service based on a set of attributes that I pass to it. I am wanting to yield these results from my Intermediate class up to the next

On Tue, Sep 24, 2013 at 4:44 PM, Nick Kledzik <kledzik at apple.com> wrote: > > On Sep 24, 2013, at 4:07 PM, Sean Silva <chisophugis at gmail.com> wrote: > > On Tue, Sep 24, 2013 at 4:17 PM, Nick Kledzik <kledzik at apple.com> wrote: > >> >> On Sep 24, 2013, at 12:40 PM, Michael Spencer <bigcheesegs at gmail.com> >> wrote: >> >>

I recently needed the behavior of my object to change on subsequent method calls so I added the syntax above. Here''s the diff of changes I made: Index: test/mocha/expectation_test.rb =================================================================== --- test/mocha/expectation_test.rb (revision 854) +++ test/mocha/expectation_test.rb (working copy) @@ -95,6 +95,12 @@

hello, I am doing PCA in R using some habitat factors, and I used the function result1=rda() and result2=princomp(),then pick up scores of the result1 and result2 using scores(),but the scores are significantly different,i do not know the meaning of it. Best wishes! Cheng

Hi all, I have a large dataset that has >10k entries. The dataset is stored in a dataframe with the headers: SubID Condition1 Condition2 Result1 Result2 There are multiple entries for a given SubID(Subject ID). Condition 1 has 3 levels and condition2 has 2 levels (therefore there are 6 possible combinations all together e.g. Cond1 Level1 x Cond2 Level 1 etc.) and i need to compute for 1. The

Dear R helpers I have following data.frame and for each product_name, I have associated mean and standard deviation. I need to generate 1000 random no.s for each of these products and find the respective mean and standard deviation.   My R code is as follows.   library(plyr) library(reshape2)   filtered_new <- data.frame(product_name = c("P1", "P2", "P3",

On Mon, Feb 23, 2009 at 2:13 PM, Jon Harrop <jon at ffconsultancy.com> wrote: > Moreover, I now have evidence that LLVM is not behaving as you expect: > > 3. Adjusting the return value from this function into sret form results in > tail call elimination being performed correctly. Note that this is still > passing a first-class struct by value as an argument to a function

Hello, I am very new to R and Time Series. I need some help including R codes about the following issues. I' ll really appreciate any number of answers... # I have a time series data composed of 24 values: myinput = c(n1,n2...,n24); # In order to make a forecasting a, I use the following codes result1 = arima(ts(myinput),order = c(p,d,q),seasonal = list(order=c(P,D,Q))) result2 =

First I am having a couple challenges with your script here: On 09/03/2015 02:43 PM, Rowland Penny wrote: > > I thought that might be your next question, I wrote it, based on what > I found here: > > http://blog.michael.kuron-germany.de/2011/02/isc-dhcpd-dynamic-dns-updates-against-secure-microsoft-dns/ > > > #!/bin/bash > > # /usr/local/sbin/dhcp-dyndns.sh > #

Hello, R users, I applied segmented regression method contributed by Muggeo and got different slope estimates depending on the initial break points. The results are listed below and I'd like to know what is a reasonable approach handling this kinds of problem. I think applying various initial break points is certainly not a efficient approach. Is there any other methods to deal with segmented

my reproducible example test<-structure(list(site = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L), .Label = c("A", "B", "C", "D", "E"), class = "factor"),

Hi, I am trying to create an R interface for Dynare++ [1], a k-order solver for rational expectation models. I would like some advice on how to glue the C++ code to R. In C++, it works the following way: - a DynareModelEq object is initialized with the formulas, parses them and performs k-order symbolic expansions - the user calls a member of this object multiple times with parameter