similar to: Collapsing across trials

Sorry to keep posting but I want to do this right and I'm hoping for some pointers I now have two time series objects which I need to subtract. Unfortunatly the two series dont have the same sample rates. When I try to subtract them avgSub<-avg1-avg2 The time series object is clever enough to object. So I guess I need to write a function for subtraction of the time series objects which

Is this what you want? temp<-c(rep("Low",2),rep("Medium",2),rep("High",2)) light<-rep(c("Dark","light"),3) avg<-dat.avg2[,3] # se<-dat.avg2[,4] dat.avg.temp<-data.frame(cbind(avg,se)) dat.avg.temp<-data.frame(cbind(temp,light,dat.avg.temp)) dat.plot<-qplot(light,avg, fill=factor(temp),data=dat.avg.temp, geom="bar",

Dear helpers, FYI, I am a beginner of R, just have dealt with MATLAB or JAVA. I want to know how to solve one problem given 4 variables: year_1, year_2, tall_1, tall_2. The tall_1 is measured at year_1 and tall_2 at year_2. The tall has grown up such as uniformly 1 cm/yr. The data is like year_1 year_2 tall_1 tall_2 2007 2010 12 15 1999 2009 6 16 2003 2005 11 13

I'm trying to collapse the following table along the sub-group factor. In this case, collapsing means taking the average ages within a subgroup and creating a new table. I seem to be running into trouble trying to create this new data frame. I can use the ave() function to find averages within a subgroup but how do I maintain the Group/Gender factors after collapsing? (see bottom table) Can

Hello all. I have a problem with collapsing by a key in a compound database. I have 2 databases (e.g. clients and client branches), both of them have the same attribute (with the same valueno), `client_id'. What I need is to search in both these databases and collapse results by `client_id' to get client IDs (set_collapse_key is used with collapse_max=1). The problem is that I receive 2

Hello list, I have a problem with the value of the result size ($msize in omegascript) when collapsing results. The index contains 151452 documents. I'm using Omega 1.0.18 on FreeBSD (I tried both the version in ports and the latest one from xapian.org). This is my indexscript: uniqueid: boolean=Q unique=Q field=uniqueid objectid: field=objectid boolean=XID value=0 objecttype: field=type

This is probably an easy question. I want to join the elements of a list/array into a single scalar value. How can I do this? More Background: I have sql queries stored in external flat text files. When I read these queries into R using the normal functions, I get a list where each line is an element in the list. When I try to pass this to the appropriate RODBC function, I get an errror.

All, When plotting a group data object, is there a way to have the plots of all the groups collapsed onto one plot, i.e., instead of separate panels as would be produced from example below? grouped.data.example <- groupedData(Y ~ Time | Patient_no, data = example.frm) plot(grouped.data.example) cheers, dave ps - I'm on windows

Hi, Here are two different ways to create a 0 x 0 logical matrix: m1 <- matrix(nrow=0, ncol=0) m1 # <0 x 0 matrix> m2 <- as.matrix(data.frame()) m2 # <0 x 0 matrix> Surprisingly: identical(m1, m2) # [1] FALSE That's because of their dimnames: dimnames(m1) # NULL dimnames(m2) # [[1]] # NULL # # [[2]] # NULL More

Dear R-helpers, I've been thinking about this for some time, maybe someone can help. I have a fairly large dataset with thousands of firms, call the a, b, c, etc.. such as [,1] [,2] [1,] "A" 0.5 [2,] "" 0.2 [3,] "" 0.3 [4,] "B" 0.1 [5,] "" 0.9 [6,] "C" 0.4 Or to put it differently two vectors such as y

Hi list, I'm currently processing textual data and I would really appreciate some help with one off my problems. I have a set of strings and I want to count how often each of this strings appears in this set. This is not very difficult and can be done as: TB<-table(my_set) plot(TB) However, I also want to collapse across sub-strings. This is, I want a sub-string ss of string S to be

Hello, Given a list with all elements having identical layout, e.g.: l = NULL l[[1]] = list(4, "hello") l[[2]] = list(7, "world") l[[3]] = list(9, " !!!! ") is there an easy way to collapse this list into a data.frame with each row being the elements of the list ? I.e. in this case I want to convert the list into a data.frame with 3 rows and 2 columns, where

Hi, Suppose I have a categorical variable called STREET, and I have 30 levels for it (i.e. 30 different streets). I want to find all those streets with only 15 observations or below then collapse them into a level called OTHER. Is there a quick way, other than using a for() loop, to do it? Currently what I'm doing is something like: ### Collapse STREET (those < 15) st <- c()

You could break your 3 class problem into several (2 or 3) 2 class problems, and then use Andy's suggestion (see the CART book). There are several ways to break the problem into 2 class problems, and several ways to combine the resulting classifiers. Tom Dietterich, Jerry Friedman, Trevor Hastie and Rob Tibshirani, among others, have articles on the question, in places like Annals of

Hello r-help, I am trying to collapse or aggregate 'some' of a data frame. A very simplified version of my data frame looks like: > tester trip set num sex lfs1 lfs2 1 313 15 5 M 2 3 2 313 15 3 F 1 2 3 313 17 1 M 0 1 4 313 17 2 F 1 1 5 313 17 1 U 1 0 And I want to omit sex from the picture and just get an addition of num,

> x <- factor(1:3, labels = c("b" , "f", "minus")) > x [1] b f minus Levels: b f minus I want to change all "minus" to "b". I know that the simplest way to do this is > levels(x) <- c("b", "f", "b") and also that > x[x == "minus"] <- "b" > x <- factor(x)

> x <- factor(1:3, labels = c("b" , "f", "minus")) > x [1] b f minus Levels: b f minus I want to change all "minus" to "b". I know that the simplest way to do this is > levels(x) <- c("b", "f", "b") and also that > x[x == "minus"] <- "b" > x <- factor(x)

I have two large datasets (156K and 2.06M records). Each row has the hour that an event happened, represented by an integer from 0 to 23. R's histogram is combining some data. Here's the command I ran to get the histogram: > histinfo <- hist(crashes$hour, right=FALSE) Here's histinfo: > histinfo $breaks ?[1] ?0 ?1 ?2 ?3 ?4 ?5 ?6 ?7 ?8 ?9 10 11 12 13 14 15 16 17 18 19 20 21

Op 29-01-15 om 00:00 schreef Gordon Messmer: > On 01/28/2015 12:12 PM, Patrick Bervoets wrote: >> >> ARPING 192.168.1.15 from 0.0.0.0 br0 >> Unicast reply from 192.168.1.15 [AC:16:2D:72:67:D4] 0.723ms >> Sent 1 probes (1 broadcast(s)) >> Received 1 response(s) >> >> Thanks anyway > > I'm not sure what you mean by "thanks anyway".

Hello I have a data frame like this: dput(states) structure(list(Date = c("24/07/2012", "25/07/2012", "26/07/2012", "27/07/2012", "28/07/2012", "24/07/2012", "25/07/2012", "26/07/2012", "27/07/2012", "28/07/2012"), State = c(1L, 1L, 1L, 1L, 1L, -1L, -1L, -1L, 1L, -1L)), .Names = c("Date",