similar to: using ddply but preserving some of the outside data

Hi R-helpers, I have been struggling with calculating row and column statistics, e.g. standard deviation. I know that > datac$Mean<-rowMeans(datac,na.rm=TRUE) will give me row means. I have tried to replicate those row means with the apply function: > datac$Mean2<-apply(datac,2,mean) so that I can replace the function argument with "sd" (instead of mean) to get standard

Dear list, I'm currently trying to use the rms package to get predicted ordinal responses from a conditional ratio model. As you will see below, my model seems to fit well to the data, however, I'm having trouble getting predicted mean (or fitted) ordinal response values using the predict function. I have a feeling I'm missing something simple, however I haven't been able to

Hi all: I have a question about lm on t-test. data(sleep) I wanna perform t-test to test the difference between the 2 groups: I can use: t.test(extra~group) The t.test result shows that:t = -1.8608; mean1=0.75,mean2=2.33 But I still wanna use: summary(lm(extra~group)) Intercept=0.75,which is mean1,just the same as t.test. group2=1.58 means the difference of the 2 groups,so

I want to obtain a barplot with error bars and a mean plot with error bars with other scale on the left in the same plot. I need help to get the same x axis (centered) when overlay two plots (barplot2 and plotCI (or lineplot.CI) with errorbars), with diferent y axis. I use par (new=T) but the X axis names are not centered with the figures. An example of my data:

I have a rather basic question. How can I get R to generate a ANOVA table and a f-value for a hypothesis test such as: Data: group1 values: 5.2 4.5 6.0 6.1 6.7 5.8 group2 values: 6.5 8.0 6.1 7.5 5.9 5.6 ... H0: mean1 = mean2 = mean3 = mean4 HA: at least two means different where I want to evaluate using a f test statistic? F = MSTr/MSE I'd like a table similar to one that

Dear R-Helpers: I am using trying to use *ddply* to extract min and max of a particular column in a data.frame. I am using two different forms of the function: ## var_name_to_split is a string -- something like "var1" which is the name of a column in data.frame ddply( df, .(as.name(var_name_to_split)), function(x) c(min(x[ , 3] , max(x[ , 3]))) ## fails with an error - case 1 ddply(

Hi, I am confused by results from: > ddply(aa, names(aa), colwise(sum)) I thought ddply was just calling colwise(sum)() with each column. However ddply() returns a 13 x 5 result !! The general result I expected is similar to that of apply() , or using colwise(sum)() alone. Shouldn't ddply() produce the same ? Thanks in advance for your help, - Stuart Andrews >

I have a dataframe df with two columns x and y. I want to count the number of times a unique x, y combination occurs. For example x<- c(1,2,3,4,5,1,2,3,4) y<- c(1,2,3,4,5,1,2,4,1) df<-as.data.frame(cbind(x, y)) #what is the correct way to use ddply for this example? ddply(df, c('x','y', summarize, ??) #desired output -- format and order doesn't matter # (x, y)

I'm trying to use ddply to compute summary statistics for many variables splitting on the variable site. however, it seems to work fine for mean() but if i use max() or min() things fall apart. whats going on? test.set<-data.frame(site=1:10,x=.Random.seed[1:100],y=rnorm(100)) means<-ddply(test.set,.(site),mean) means site x y 1 1 -97459496 -0.14826303 2

Dear All I want to generate variable with Bivariate Normal Distribution by use mean1 = a, variance1 = b, mean2 = c, variance2 = d, rho = e. How I can do this. Many Thanks. IRD [[alternative HTML version deleted]]

While putting my R code into functions, I've encountered a ddply function nesting issue and need a bit of advice on the proper way to fix it.? I've tried several approahces, but neither worked and I need to have the ability to include the "cut", "range", and "fullseq" methods within ddply.? (For a bit of that explanation refer to

Hello everyone, I was asked to repost this again, sorry for any inconvenience. I'm looking replacement for ddply function from plyr package. Function allows to apply function by category stored in any column/columns. Regular loops or lapplys slow down greatly because my unique combination count exceeds 9000. Is there any available solution which allow me to apply function by category?

Hello, all. I'm new to R and just beginning to learn to write functions. I know I'm out of my depth posting here, and I'm sure my issue is mundane. But here goes. I'm analyzing the American National Election Study (nes), looking at mean values of a numeric dep_var (environ.therm) across values of a factor (partyid3). I use ddply from plyr and wtd.mean from Hmisc. The nes requires a

Hi all, I have a data set (df, n=10 for the sake of simplicity here) where I have two continuous variables (age and weight) and I also have a grouping variable (group, with two levels). I want to run correlations for each group separately (kind of similar to "split file" in SPSS). I've been experimenting with different functions, and I was able to do this correctly using ddply

Hi, I am really confused how ddply work, so maybe you can help me. I created a function that sorts a vector etc. fn <- function(x){ x1 <- sort(x) x2 <- seq(length(x)) x3 <- x2/max(x2) df <- data.frame(x1,x2,x3) df } Probably this is not the best form of the function, but at least it produces what I want (data to plot a cumulative count curve). This function works on a

Dear group, Here is my data frame: futures <- structure(list(DESCRIPTION = c("CORN Jul/10", "CORN Jul/10", "CORN Jul/10", "CORN Jul/10", "CORN Jul/10", "LIVE CATTLE Aug/10", "LIVE CATTLE Aug/10", "SUGAR NO.11 Jul/10", "SUGAR NO.11 Jul/10", "SUGAR NO.11 Jul/10", "SUGAR NO.11

An embedded and charset-unspecified text was scrubbed... Name: inte tillg?nglig URL: <https://stat.ethz.ch/pipermail/r-help/attachments/20120303/a62e41f2/attachment.pl>

Dear all! After hours of trying around, I gave up: I have a 2-dimensional array, and I know how to split it into its rows and how to get the mean for every row using 'sapply'. But what I want is to calculate the mean over the first n rows, and then the second n rows, etc., so that I get a vector like: v == mean1(row 1:5), mean2(row6:10),... (trivial, you might say. I find it rather

Dear R-users, I am trying to get the plyr syntax right, without much success. Given: d<- data.frame(cbind(x=1,y=seq(20100801,20100830,1))) names(d)<-c("first", "daterep") d2<-d # I can convert the daterep column in place the classic way: d$daterep<-as.Date(strptime(d$daterep, format="%Y%m%d")) # How to do it the plyr way? ddply(d2,

Dear all, I am encountering problems with the application of ddply within the body of a self-defined function. The script is the following: moncostcarmoto <- function(costtype){ costaux_result <- data.frame() for (purp in PURPcount){for (per in PERcount){ costcarin =