similar to: Help on running regression by grouping firms

Dear R-user, a few weeks ago I consulted the list-serve with a similar question. However, my task changed a little but sufficiently to get lost again. So I would appreciate any help on the following issue. I use the plm package and work with firm-level data in a panel. I would like to eliminate all firms that do not fulfill the requirement of having an observation in every variable used for at

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

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, 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

dear R wizards:? I am wrestling with reshape.? I have a long data set that I want to convert into a wide data set, in which rows are firms and columns are years. > summary(rin) firm fyear sim1 Min. :1004.00 Min. :1964.0 Min. : -1.00000 1st Qu.:1010.00 1st Qu.:1979.0 1st Qu.: -0.14334 Median :1016.00 Median :1986.0 Median : 0.00116 Mean

Dear R helpers, I know R language at a preliminary level. This is my first post to this R forum. I have recently learned the use of function and have been successful in writing few on my own. However I am not able to figure out how to apply the function to multiple sets of data. # MY QUERY Suppose I am having following data.frame df = data.frame(k = c(1:8), ratings = c("A",

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-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

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",

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,

Hi all, I have a data set that looks a bit like this. feed1 RFU Site Vial Time lnRFU 1 44448 1 1 10 10.702075 2 47521 1 1 20 10.768927 3 42905 1 1 30 10.66674 4 46867 1 1 40 10.755069 5 42995 1 1 50 10.668839 6 43074 1 1 60 10.670675 7 41195 1 1 70 10.626072 8 47090 1 2 10 10.759816 9 48100 1

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've records like this df= x panel 4 1 93 2 21 3 83 4 75 1 87 2 87 3 78 4 50 1 76 2 86 3 65 4 84 1 40 2 39 3 26 4 i want to create histogram out of it . i want all the mid and count values for panel wise my code is histoutput = ddply(df,.(df[2]),hist) i'm not able to get the required result. please help me using for loop takes a lot of time if there are more records ----- Thanks

Trying to use dates in their R-native form (e.g., POSIXct) rather than turning them into character strings, I've encountered the following problem. I create a data frame where one column is dates. Then I use "by()" to do a calculation on grouped subsets of the data. When I try to extract values from the result, I get "subscript out of bounds". The example below shows the

Hello, I am using the following script to run an anova for numerous species in a table that I have: SiteSpp <-

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

Hello R users, This is more of a convenience question that I hope others might find useful if there is a better answer. I work with large datasets that requires multiple parsing stages for different analysis. For example, compare group 3 vs. group 4. A more complicated comparison would be time B in group 3 of group L with B in group 4 of group L. I normally subset each group with the

Hello All, Recently developed the code below for graphing patterns of chemotherapy administration. As someone just starting to use R in their work, I managed to figure out some parts of the code but needed help with others. setwd("N:/Regimen Coding/0906/Plots Test") getwd() TestData <- structure(list(profile_key = c(1, 1, 1, 1, 1, 2, 2, 2, 2, 2, 2, 3, 3, 3, 3, 3), line = c(1, 1,

Hello R community, I am computing weighted average statistic by using ddply function: My data set is: N1 T1 S1 I1 C1 FY-4 ROE11 EPS11 MKT11 N1 T1 S1 I1 C1 FY-3 ROE12 EPS12 MKT12 N1 T1 S1 I1 C1 FY-2 ROE13 EPS13 MKT13 N1 T1 S1 I1 C1 FY-1 ROE14 EPS14 MKT14 N1 T1 S1 I1 C1 FY0 ROE15 EPS15 MKT15 N1 T1 S1 I1 C1 FY1 ROE16 EPS16 MKT16 N1 T1 S1 I1 C1 FY2 ROE17

Dear all, I?m having trouble getting a list of regression variables back into a dataframe. mydf <- data.frame(x1=rnorm(100), x2=rnorm(100), x3=rnorm(100)) mydf$fac<-factor(sample((0:2),replace=T,100)) mydf$y<- mydf$x1+0.01+mydf$x2*3-mydf$x3*19+rnorm(100) dlply(mydf,.(fac),function(df) lm(y~x1+x2+x3,data=df))->dl here I?d like to use ldply(dl,coef(summary)) or something