similar to: Problem with ldply

Hello R User, I was trying to display r.squared and p value in table from regression, but I could not display these parameters in the table (matrix) for example individual <- c(1,1,6,8,8,9,9,9,12,12) day <- c(4,17,12,12,17,3,9,22,13,20) condition <- c(0.72, 0.72, 0.67, 0.73, 0.76, 0.65, 0.68, 0.78, 0.73, 0.71) test <- data.frame(individual, day, condition) ind.id <-

json_dir is a list of JSON lists mapping lat/long route points between locations using CloudMade's API. post_url is the URL of the HTTP request for (n in json_dir) { i = i + 1 if (typeof(json_dir[[i]]) != "NULL") { if (i == 1) { dat_add <- ldply(json_dir[[i]], function(x) t(data.frame(x)), .progress = "text")

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

In glm() you can use the summary() function to recover the shape parameter (the reciprocal of the dispersion parameter). How do you recover the scale parameter? Also, in the given example, how I estimate and save the geometric mean of the predicted values? For a simple model you can use fitted() or predicted() functions. I will appreciate any help. ? ? ? #Call required R packages require(plyr)?

> On Apr 17, 2018, at 10:10 AM, Allaisone 1 <allaisone1 at hotmail.com> wrote: > > > Hi all > > I have a list of multiple datframes with the same column headers. The last column in each datframe contains a vector of "Interval" class after I have produced this column using "lubridate" package. I needed to convert my list of dataframes to be in a single

Hi all I have a list of multiple datframes with the same column headers. The last column in each datframe contains a vector of "Interval" class after I have produced this column using "lubridate" package. I needed to convert my list of dataframes to be in a single dataframe for further analysis. I did this using the following syntax : SingleDataframe <- ldply

dear all, apologizes for bothering with a probably stupid question but I really don' t know how to proceed. I have a dataset which look like df a <- c(1,2,3,4,4,4,5,5) b <- c(11,7,4,9,8,3,12,4) df <-cbind(a,b) I would like to have one which looks like this: a 1 11 2 7 3 4 4 9 8 3 5 12 4 a are vertex of a network, b the edges. In the data the lenght of a is about 50000 I read

Happy weekend helpeRs! As usual, I'm stumped by R... My plan was to take an integer number, convert it to binary and wind up with a data.frame where each column is either 1 or 0 so I can see which bits are changing: bb<-function(i) ifelse(i, paste(bb(i %/% 2), i %% 2, sep=""), "") my.dat<-c(36,40,10,4) my.binary.dat<-bb(my.dat)

hey, folks, I have two very simple questions. I am not quite sure if I can do this using R. so, I am analyzing a large data frame with thousands of variables. For example: Dependent variables: d1, d2, d3 (i.e., there are three dependent variables) Independent variables: s1, s2, s3, ......s1000 (i.e., there are 1000 independent variables) now I want to run simple linear regression analyses of

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

Hello R Community, I don't post to these things often so excuse me if I stumble on my forum etiquette. This is a complex problem for me, which may require two forum entries, but I will try my best to be concise. Also, I am a self taught coder, so if my code is not to convention, your constructive criticism is always welcome. I need to split up a data frame by participant (gpsarc -

Hi all, I have the next problem: I have a matrix with size 8,000,000x18. My personal computer...blocks...so I have cut my original file into 100 different file. I have written a function that should be run on each of this file. So imagine I need to read data from q1 to q100 file data<-read.table("q1.txt",sep="") and each time I read 1 file execute my personal function

for example : I have files with the name "ma01.dat","ma02.dat","ma03.dat","ma04.dat",I want to read the data in these files into one data.frame flnm<-paste("obs",101:114,"_err.dat",sep="") newdata<-read.table(flnm,skip=2) data<-(flnm,skip=2) but the data only contains data from the flnm[1] I also tried as below : for

Hi there, I ran the following code: vols=read.csv(file="C:/Documents and Settings/Hugh/My Documents/PhD/Swaption vols.csv" , header=TRUE, sep=",") X<-ts(vols[,2]) #X dcOU<-function(x,t,x0,theta,log=FALSE){ Ex<-theta[1]/theta[2]+(x0-theta[1]/theta[2])*exp(-theta[2]*t) Vx<-theta[3]^2*(1-exp(-2*theta[2]*t))/(2*theta[2]) dnorm(x,mean=Ex,sd=sqrt(Vx),log=log) }

Hi I would like to shorten mod1 <- nls(ColName2 ~ ColName1, data = table, ...) mod2 <- nls(ColName3 ~ ColName1, data = table, ...) mod3 <- nls(ColName4 ~ ColName1, data = table, ...) ... is there something like cols = c(ColName2,ColName3,ColName4,...) for i in ... mod[i-1] <- nls(ColName[i] ~ ColName1, data = table, ...) I am looking forward to help Christof

I need to run binomial tests (binom.test) on a large set of data, stored in a table - 600 tests in total. The values of x are stored in a column, as are the values of n. The data for each test are on a separate row. For example: X N 11 19 9 26 13 21 13 27 18 30 It is a two-tailed test, and P in all cases is 0.5. My question is: Is there a quicker way of running these tests without having to

Hi group, I imported 16 data frames using the function "list.files" temp <- list.files(path="...........") myfiles = lapply(temp, read.table,sep = "") Now I have 16 data set imported in R window. I want to combine them by row and tried some thing like (Here I am considering only 20 columns) for(i in 1:16){ data<- cbind(myfiles[[i]][,1:20]) } but it

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,

Hi, everybody: I asked about this in r-help last week and promised a summary of answers. Special thanks to the folks that helped me understand do.call and pointed me toward plyr. We face this problem all the time. A procedure generates a list of data frames. How to stack them together? The short answer is that the plyr package's rbind.fill method is probably the fastest method that is not

Dear List, I'm trying to use different R packages for my Teaching Assistantship classes. And I cam out to an (apparently) very simple problem. I would like to retrieve the vertices coordinate of a SpatialPolygon data. I know this is stored in the "coords" slot, but I can't get access to it! I tried to coerce the SpatialPolygon into a data.frame but it doesn't work.