similar to: How to filter an activerecord find_all...

Dear R-ers, In my question there are no statistics involved - it's all about data manipulation in R. I am trying to write a code that should replace what's currently being done in SAS and SPSS. Or, at least, I am trying to show to my colleagues R is not much worse than SAS/SPSS for the task at hand. I've written a code that works but it's too slow. Probably because it's

Hello. I know how to make a bar plot in which a numeric y variable is plotted against some grouping variable X (say, groups A, B, C) when this grouping variable is subdivided into each of two subgroups; so the bars would be: (group A subgroup 1) beside (group A subgroup 2), then (group B subgroup 1) beside (group B subgroup 2), and so on. This is done using the beside=TRUE argument in the

Another newbie question: How do i convert a float to a string, rounded to a certain number of decimals? Thanks -- Posted via http://www.ruby-forum.com/.

Hello, I'm using the rmeta package to perform a meta analysis using summary statistics rather than raw data, and would like to analyze the effects in three different subgroups of my data. Furthermore, I'd like to plot this on one forest plot, with corresponding summary weighted averages of the effects displayed beneath each subgroup. I am able to generate the subgroup analyses by simply

Hi, Is there is any way in ruby on rails where we show all my groups there subgroups with check boxes in tree structure way? e.g group A | ----Group A.1 | ----Group A.2 | ---------Group A.2.1 All with check boxes and subgroup opens when click on root ? -- Posted via

Hi, I have a data.frame with many variables for which I am performing the mean by subgroup, for a pair of variables at a time, where one of them for each pair defines the subgroup. The subgroups in the x$cm1 are 0, 1 and 2. x ph1 cm1 0.2345 2 1.2222 1 2.0033 0 0.0000 2 1.0033 1 0.2345 0 1.2222 2 2.0033 0 0.0000 1 1.0033 2 > meanbygroup <- as.vector(with(x, by(x$ph1, x$cm1, mean)))

Dear Members of the R-Help, While using a R function - 'aggregate' that you developed, I become to have a question. In that function, > aggregate(x, by, FUN, ..., simplify = TRUE) I was wondering about what type of FUN I should write if I want to get "the most frequent value of the subgroup" as a summary statistics of the subgroups. I will appreciate if I can get

Dear R-users, I want to multiple impute missing scores, but only for a few subgroups in my data (variable 'subgroups': only impute for subgroups 2 and 3). Does anyone knows how to do this in MICE? This is my script for the multiple imputation: imp <- mice(data, m=20, predictorMatrix=pred, post=post, method=c("", "", "", "",

Hi All, Is there a feasibility for creating subgroups on the Puppet Dashboard? Basically the requirement is that we have a huge number of VMs running designated services. Some of VMs having the same service may yet have different properties configured on them. We are exploring the feasibility of having these properties managed through puppet. Currently all these VMs are put into a single

With this mail I would like to make a proposal to add additional informations to the core and plugin metadata files. Currently these tags are already handled in the ccs configuration system. Ccs automatically adds this informations to the core/plugin option set, but I think that it would make more sense to add this to the official files, to allow similar features in other configuration

Dear users of metafor, I am working on a meta-analysis using the metafor package. I have a excel csv database that I am working with. I am interested in pooling the effect measures for a particular subgroup (European women) in this csv database. I am conducting both sub-group and meta-regression. In subgroup-analyses, I have stratified the database to create a separate csv file just for European

I have: @pictures=@c.pictures How do I add limit and order_by conditions. I have tried the following: @c.pictures.find_all(:limit=>5) @c.pictures, :limit=>5 @c.pictures :limit=>5 None of these work. -- Posted via http://www.ruby-forum.com/.

Using the survival library, it is possible to get a plot of all the subjects in a sample and it is possible to get a plot of all subgroups in the same plot. How does one get a separate plot for each subgroup? plot(survfit(Surv(time,death==1)~group),col=1:10) The above results in a hideous graphic representation. I would prefer to specify par(mfrow = c(2, 5)) and have each plot separately --

On Fri 2015-06-12 01:52:54 -0400, Mark D. Baushke wrote: > I have communicated with Allen Roginsky on this topic and I have been given permission to post his response. > > In this message below, the 'vendor' was Darren Tucker's generated prime > that used a generator value of 5. > > -- Mark > > From: "Roginsky, Allen" <allen.roginsky at

Hi folks, I have a dataframe df.vars with the follwing structure: var1 var2 var3 group Group is a factor. Now I want to standardize the vars 1-3 (actually - there are many more) by class, so I define z.mean.sd <- function(data){ return.values <- (data - mean(data)) / (sd(data)) return(return.values) } now I can call for each var z.var1 <- by(df.vars$var1, group,

On Wed 2015-05-27 05:23:41 -0400, Hubert Kario wrote: > On Tuesday 26 May 2015 15:10:01 Daniel Kahn Gillmor wrote: >> On Tue 2015-05-26 14:02:07 -0400, Hubert Kario wrote: >> > OEIS A014233 >> >> Hm, this is a sequence, but not an algorithm. It looks to me like it is >> not exhaustive, just a list of those integers which are known to have >> the stated

I have the following formula for a linear model: z <- lm(y~x + factor(a) + factor(b), data=NT2010) where a (groups) and b (Sub-groups) are categorical variables (factors), x is a continuous covariate, and y the response variable. Since b is nested within a, the formula can also be written as: z <- lm(y~x + factor(a) + factor(a)/factor(b), data=NT2010) and the same output is achieved

Hi. In a data set I have a variable that takes values from 1 to 14. For each subgroup of values of this variable, I would like to obtain some descriptive statistics of other variables present in the data set. I've been trying with a "for" loop but I couldn't get nothing. Could you please suggest me some lines? -- View this message in context:

Hi all, LLVM needs a solution to the long-standing problem that the IR is unable to express certain semantics expected by high-level programming languages that target GPUs. Solving this issue is necessary both for upstream use of LLVM as a compiler backend for GPUs and for correctly supporting LLVM IR <-> SPIR-V roundtrip translation. It may also be useful for compilers targeting

# Dear all, # how to replace values in x by means in subgroups created in ... # replace only these values where y=0 in continous sequence # replace by mean calculated locally for each subgroup created by # continous sequence of 0,0,0 in parallel y vector, i.e. # where there is continous sequence of 0 in data frame vector y # but we do not replace values in x[i], if y[i]!=0 # we do not want