similar to: Bug in by() with dates as levels?

Full_Name: Oren Cheyette Version: 2.7.2 OS: Win XP Submission from: (NULL) (64.161.123.194) Enter the following at the R command prompt: > sprintf("A %S %S %S XYZ", 1, 1, 1); Note the erroneous capitalized %S instead of %s and the numeric inputs instead of strings. With strings there's no crash - R reports bad format specifications.

I'm running R 2.9.1 on winXP, using the library plyr. Can anyone explain to me what is going wrong in this code? (in particular see lines marked with ******************) Trying to modify objects in a list created using dlply seems to corrupt the objects in the list. > library(plyr) > d=as.data.frame(cbind(c(1,1,1,2,2,2),c(1,2,3,4,5,6))) > d V1 V2 1 1 1 2 1 2 3 1 3 4 2 4 5

Dear all, I'm stuck with a problem using plyr to process a rather large junk of data. What I'm trying to do is applying a moving average to all the subparts of the dataframe (the example data can be found here https://dl.dropboxusercontent.com/u/2414056/testData.Rdata). require(plyr) load("testData.Rdata") applyfilter<-function(x){ return(filter(x,rep(1/5, times=5))) }

Hi, I have a dataframe basically like this: > head(asturias.gen2011[,c(1,4,9:14)]) municipio total upyd psoe pp iu fac tipo 440 Allande 2031 1.44 31.10 39.75 4.01 21.62 1000-10000 443 Aller 12582 1.37 33.30 37.09 15.53 10.35 10000-50000 567 Amieva 805 1.48 32.69 37.36 6.15 20.16 <1000 849

Hi there, I have a huge data set with multiple firms years and other firm characteristics. I want to run a regression on the dependent variable and other explanatory variables and calculate the residual terms by grouping the firms in same year and same industry. What I want to do is to divide my obseravtion into sub sample that contains the observation with same fiscal year(FYEAR=1990) and same

Dear R-users, I want to plot residuals vs fitted for multiple groups with ggplot2. I try this code, but unsuccessful. library("plyr") models<-dlply(dat1,"d",function(df) mod<-lm(y~x,data=df) ggplot(models,aes(.fitted,.resid), color=factor(d))+ geom_hline(yintercept=0,col="white",size=2)+ geom_point()+ geom_smooth(se=F) -- --- Catalin-Constantin ROIBU

Inthe code below I was trying to to obtain the GMM estimates for CAPM (REGRESSION) for 36 stocks each have 180 observations,however it only gives me one output rather than 36. In SAS i would just put in a *By statement*. I have a variable TICKER that categorize them into 36 groups. *How can I obtain all 36 output instead of just one.* **

Dear R helpers, (At the outset I sincerely apologize if I have not put forward my following query properly, though I have tried to do so.) Following is a curtailed part of my R - code where I am trying to generate say 100 random no.s for each of the products under consideration. library(plyr) n = 100 my_code = function(product, output_avg, output_stdev)     { BUR_mc = rnorm(n, output_avg,

I have a simple 1 way anova coded like summary(ANOVA1way <- aov(Value ~ WellID, data = welldata)) How can I use the BY function to do this ANOVA for each group using another variable in the dataset?? I tried coding it like this, but it doesn't seem to work. summary(ANOVA1way <- by(welldata, Analyte, function(x) aov(Value ~ WellID, data = welldata))) In SAS I would code it like this:

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",

I'm having a hard time figuring out how to group results by certain factors in R. I have data with the following headings: [1] "Time" "Plot" "LatCat" "Elevation" "ElevCat" "Aspect" "AspCat" "Slope" [9] "SlopeCat" "Species" "SizeClass" "Stems" and

Hi List, I have the following problem: I am using the multilevel package and make.univ function for available in the package and then xyplot from lattice and I want to know how could I be able to use the ?coefficient? for the straight line that passes the data ? Example from help: library(multilevel) data(univbct) #a data set already in univariate or stacked form for job satisfaction

Dear All Sorry for this simple question, I could not solve it by spending days. My data looks like this: # data set.seed(1234) clvar <- c( rep(1, 10), rep(2, 10), rep(3, 10), rep(4, 10)) # I have 100 level for this factor var; yvar <- rnorm(40, 10,6); var1 <- rnorm(40, 10,4); var2 <- rnorm(40, 10,4); var3 <- rnorm(40, 5, 2); var4 <- rnorm(40, 10, 3); var5 <- rnorm(40, 15,

* On 2008-11-13 at 18:51 -0500 Duncan Murdoch wrote: > On 12/11/2008 8:30 PM, ocheyett at bonddesk.com wrote: >> Full_Name: Oren Cheyette >> Version: 2.7.2 >> OS: Win XP >> Submission from: (NULL) (64.161.123.194) >> >> >> Enter the following at the R command prompt: >>> sprintf("A %S %S %S XYZ", 1, 1, 1); >> >> Note the

Hi, I have this sample data below and would like to create a list of matricies. setseed(1254) id <- c(1,1,1,1 ,2,2,2) o <- as.factor(c(1:4, 1, 3, 4)) r <- rep(.5, 7) v <- rnorm(7) s <- rnorm(7) dat <-data.frame(id, o, r, v, s) dat #> dat # id o r v s # 1 1 0.5 0.7024631 2.0813672 # 1 2 0.5 -0.5541955 0.1095156 # 1 3 0.5 -1.0418167 0.4164930 # 1

Dear all Suppose the object below: > require(Hmisc) > require(plyr) > x <- dlply(iris, .(Species), describe) How can I print the object without displaying the attributes? I inspected ?print and ?print.default with no luck. > x $setosa x[, "Sepal.Length"] n missing unique Mean .05 .10 .25 .50 .75 50 0 15 5.006 4.40 4.59

Dear R helpers I have following two data.frames viz. equity_data and param. equity_data = data.frame(security_id = c("Air", "Air", "Air", "Air", "Air", "Air", "Air", "Air", "Air", "Air", "Air", "Air", "AB", "AB", "AB", "AB",

I?m wondering which is the most efficient (time, than memory usage) way to obtain a multivariate time series object from a data frame (the easiest data structure to get data from a database trough RODBC). I have a starting point using timeSeries or xts library (these libraries can handle time zones), below you can find code to test. Merging parallelization (cbind) is something I?m thinking at

I retrieve for a few hundred times a group of time series (10-15 ts with 10000 values each), on every group I do some calculation, graphs etc. I wonder if there is a faster method than what presented below to get an appropriate timeseries object. Making a query with RODBC for every group I get a data frame like this: > X ID DATE VALUE 14 3 2000-01-01 00:00:03 0.5726334

Hello, I'd like to produce a ggplot where the order of factors within facets is based on the average of another variable. Here's a reproducible example. My problem is that the factors are ordered similarly in both facets. I would like to have, within each facet of `f1', boxplots for 'x' within each factor `f2', where the boxplots are ordered based on the average of x