similar to: aggregate.formula implicitly removes rows containing NA

I posted this yesterday to r-help and Ben Bolker suggested reposting it here... Dickison, Daniel <ddickison <at> carnegielearning.com> writes: > > The documentation for agrep says it uses the Levenshtein edit distance, > but it seems to get this wrong in certain cases when there is a > combination of deletions and substitutions. For example: > > >

The documentation for agrep says it uses the Levenshtein edit distance, but it seems to get this wrong in certain cases when there is a combination of deletions and substitutions. For example: > agrep("abcd", "abcxyz", max.distance=1) [1] 1 That should've been a no-match. The edit distance between those strings is 3 (1 substitution, 2 deletions), but agrep matches

Dear R community Recently, dear Henrique Dallazuanna literally saved me solving one problem on data transformation which follows: (n_, _n, j_, k_ signify numbers) SOURCE DATA: id cycle1 cycle2 cycle3 ? cycle_n 1 c c c c 1 m m m m 1 f f f f 2 m m m NA 2

This relates to a message from Christophe Pallier to r-help some time ago. Like myself, he finds aggregate very useful, but the interface a little cumbersome. I've implemented a more compact formula interface, found at the bottom of this message: data(ToothGrowth) # I used to aggregate like this: aggregate(list(len=ToothGrowth$len),

Dear all, I want to use aggregate.formula to conveniently summarize a data.frame. I have quiet some variables in the data.frame and thus I don't want to write all these names by hand, but instead create them on the fly. This approach has the advantage that if there will be even more columns in the data.frame I don't have to change the code. I've hence tried to construct a formula

I'm having a problem with aggregate.formula when I call it in a function and the function is converted from a string in the funtion I think my problem may also only occur when the left hand side of the formula is cbind(...) Here is example code that generates a dataset and then the error. The first function "agg2" fails > agg2(FALSE) do agg 2 Error in m[[2L]][[2L]] : object

In the code for 'aggregate.formula', there is if (as.character(formula[[2L]] == ".")) I believe that it is meant to be if (as.character(formula[[2L]]) == ".") However, if (as.character(formula[[2L]] == ".")) gives the expected result. Tracing: - formula[[2L]] == "." is equivalent to as.character(formula[[2L]]) == "." From the help page for

Hi - I apologize for the 2nd post, but I think my question from a few weeks ago may have been overlooked on a Friday afternoon. I might be missing something very obvious, but is it widely known that the aggregate function handles missing values differently depending if a data frame or a formula is the first argument ? For example, (d<- data.frame(sex=rep(0:1,each=3),

Hello! I am aggregating using a formula in aggregate - of the type: aggregate(cbind(var1,var2,var3)~factor1+factor2,sum,data=mydata) However, I actually have an object (vector of my variables to be aggregated): myvars<-c("var1","var2","var3") I'd like my aggregate formula (its "cbind" part) to be able to use my "myvars" object. Is it

Folks, Sorry if this question has been answered before or is obvious (or worse, statistically "bad"). I don't understand what was said in one of the search results that seems somewhat related. I use aggregate to get a quick summary of the data. Part of what I am looking for in the summary is, how much influence might the NA's have had, if they were included, and is excluding

All, I've been using aggregate() to compute means and standard deviations at time/treatment combinations for a longitudinal dataset, using na.rm = TRUE for missing data. This was working fine before, but now when I re-run some old code it isn't. I've backtracked my steps and can't seem to find out why it was working before but not now. In any event, below is a reproducible

I have a two question regarding the "aggregate.data.frame" method of the "aggregate" function. My situation: a. My "x" variable is a data.frame ("mydf") with two columns, both columns of type/format "numeric". b. My "by" variable is a data.frame("mybys") with two columns, both columns of type/format "character". c.

i need help setting up the routes for my app. I have created about 10 controllers in the app/controllers/pro directory: app/controllers/pro/address_controller.rb app/controllers/pro/certification_controller.rb app/controllers/pro/program_controller.rb app/controllers/pro/program_controller.rb and so on... The problem is that I would like to also use app/controllers/pro as a controller; so

Dear r-help reader, I have some problems with the aggregate function. My datframe looks like >frame Day Time V1 V2 1 M 0 3 NA 2 M 0 4 NA 3 M 0 5 2 4 M 1 NA 4 5 M 1 10 6 6 T 0 4 45 7 T 1 4 3 8 T 1 3 2 9 T 1 6 1 I used the aggegate function to obtain the mean in V1 and V2 over the grouping variable Time and Day

Is there a way to trigger an action when a certain number of zap channels are in use, or is there a variable that stores max used channels that can be read? I use PRI for inbound calls, but outbound goes out via SIP, so the simple solution does not work. I need to know when the potential exists for inbound calls via PRI/Wildcard to be blocked because there are no more channels. Obviously

Dear All: I am trying to calculate four columns' means in a dataframe like this: FID MID IID EW_INCU EW_17.5 EMW EEratio 1 4621 TWF2H5 45.26 NA 15.61 NA 1 4621 TWF2H6 48.02 44.09 13.41 0.3041506 2 4630 TWF2H19 51.44 47.81 NA NA 2 4631 TWF2H21 NA 52.72 16.70

Hi everyone, I have a test set with more than 1000 cases, when I use evaluate_Weka_classifier(RWeka)to evaluate my classifier on this test set, the output shows me the result of only 83 cases. I do have missing values in predictors, so I tried na.acton=na.pass, but it dosen't help. Now I confused, why RWeka ignore so many cases in my test set? Is there any setting I didn't notice in

The aggregate function does "almost" all that I need to summarize a datasets, except that I can't specify exclusion of NAs without a little bit of hassle. > set.seed(143) > m <- data.frame(A=sample(LETTERS[1:5], 20, T), B=sample(LETTERS[1:10], 20, T), C=sample(c(NA, 1:4), 20, T), D=sample(c(NA,1:4), 20, T)) > m A B C D 1 E I 1 NA 2 A C NA NA 3 D I NA 3 4 C I

Any better (more efficient, built-in) ideas for computing coef[1]+coef[2]*x+coef[3]*x^2+ ... than polynom <- function(coef,x) { n <- length(coef) sum(coef*apply(matrix(c(rep(x,n),seq(0,n-1)),ncol=2),1,function(z)z[1]^z[2])) } ? Ben -- 318 Carr Hall bolker at zoo.ufl.edu Zoology Department, University of Florida http://www.zoo.ufl.edu/bolker

hi, Does factanal() force the user to use the formula interface if they wish to specify an na.action? v1 <- c(1,1,1,1,1,1,1,1,NA,1,3,3,3,3,3,4,5,6) v2 <- c(1,2,1,1,1,1,2,1,2,1,3,NA,3,3,3,4,6,5) v3 <- c(3,3,3,3,3,1,1,1,1,1,1,1,1,1,1,5,4,6) v4 <- c(3,3,4,NA,3,1,1,2,1,1,1,1,2,NA,1,5,6,4) v5 <- c(1,1,1,1,1,3,3,3,3,3,1,1,1,1,1,6,4,5) v6 <- c(1,1,1,2,1,3,3,3,4,3,1,1,1,2,1,6,5,4) m1