similar to: how to melt variable to one variable

Could anyone help with a linear mixed model fitting problem ? The model is : Y= Xp + Zu + e where X, Z are known design matrix, p is fixed effect factor, u is random effect, u~ (0, G) , e~(0,R) The main problem is , I want to fix the covariance matrix G to be a constant times a known covariance matrix A, G = c*A (c is positive constant, A is a predefined matrix with values manually set by

my dataset looked like this in the beginning: >Daten V1 V2 V3 1 Dosis Gewicht Geschlecht 2 0 6.62 m 3 0 6.65 m 4 0 5.78 m 5 0 5.63 m I need box plots for V2 with all combination of V1 and V3, so I deleted the first row, and tried this: boxplot(Daten$V2[Daten$V3=="m"]) but it does not work and I

Hello, I implemented two functions reshape_long and reshape_wide (see full working example below) to reshape data frames. I created several small examples and the two functions seemed to work properly. However, using the reshape_wide function on my real data sets (about 200.000 to 300.000 rows) failed. What happens is set all values for X, Y and Z were set to 1. The structure of my real data

Hi, Try: dat1 <- read.csv("precipitationRglimclim.csv",header=TRUE,stringsAsFactors=FALSE,sep="\t") library(reshape2) dat2M <- melt(dat1,id.var=c("year","month","day")) dat2M1 <- dat2M[with(dat2M,order(year,month,day,variable)),] ?dim(dat2M1) #[1] 1972320?????? 5 ?row.names(dat2M1) <- 1:nrow(dat2M1) ?colnames(dat2M1)[4:5] <-

Hi:I recently started using the melt function and found that it is very useful and powerful,however I can't seem to find the way to change the default column header "value" to my custom column name. Does anyone know how to go about this? any suggestions are very appreciated. Thanks Felipe D. Carrillo Fishery Biologist US Fish & Wildlife Service California, USA

I have a data frame that is the result of a cast (reshape) operation. I deleted the variable column and tried to melt the resulting data frame. Depending on which method I use to delete the column I get different error messages when melting: > head(tinfos) vpn group trial_no item relation trial_type rt variable # 1 102 2 1 4351 diag1 distractor 8471 fix_d 27

Dear R Users, I'm trying to use the reshape package to 'melt' my gridded data into column format. I've done this before on individual files, but this time I'm trying to do it on a directory of files (with variable file names) - therefore I have to also use the 'assign' command. I have come up against a couple of problems however and am therefore seeking advice... >

Hi, I have installed R on my computer with windows 7 . I also installed reshape software, but I am not being able to work with melt cast commands . I have chjecked the commands.It is not working. Thankyou, Deepika [[alternative HTML version deleted]]

I'm sorry everyone for the inconvenience of spamming the R-help... Here's the complete post: Hi everyone, > > Since it's quite a while that I used the reshape package, I now feel kind > of rusty. > > I have a data.frame like this: > > > > id Sample.Name Marker Allele.1 > Allele.2 sample_id species

I have a data frame with a number of observed and predicted values by classification as shown below: Count Volume FCLASS 1 55000 60000 Grade Separated 2 43000 39000 Grade Separated 3 26000 26500 Major Arterial 4 19500 20000 Major Arterial ... There are four classes here: Grade Separated, Major Arterial, Minor Arterial, and Collector I am looking

I have the raw data with 9 column and 197977 row: > dummy State Months Bedroom 1 xxx Jan 1 2 xxx Jan 2 3 xxx Jan 1 4 yyy Jan 1 5 yyy Jan 2 6 yyy Jan 1 7 zzz Jan 3 8 zzz Jan 1 9 zzz Jan 2 10 xxx Feb 3 11 xxx Feb 4 12 xxx Feb 2 13 yyy Feb 1 14

Simple illustration, > df3 <- data.frame(id=c(3,2,1,4), age=c(40,50,60,50), dose1=c(1,2,1,2), dose2=c(2,1,2,1), dose4=c(3,3,3,3))> df3 id age dose1 dose2 dose41 3 40 1 2 32 2 50 2 1 33 1 60 1 2 34 4 50 2 1 3> melt.data.frame(df3, id.var=1:2, na.rm=T) id age variable value1 3 40 dose1 12 2 50 dose1 23 1

## Can someone suggest a simpler expression than either of these, with the goal ## of taking a long matrix into a wide one with exactly one of the factors converted to ## columns and all the rest retained as factors. I want something that generalizes beyond ## the three factors illustrated here. ## Rich meltTest <- data.frame(A=rep(c("B","C"), each=12),

my data looks like this: PM10 Ref UZ JZ WT RH FT WR 1 10.973195 4.338874 nein Winter Dienstag ja nein West 2 6.381684 2.250446 nein Sommer Sonntag nein ja Süd 3 62.586512 66.304869 ja Sommer Sonntag nein nein Ost 4 5.590101 8.526152 ja Sommer Donnerstag nein nein Nord 5 30.925054 16.073091 nein Winter Sonntag nein nein Ost 6

Hello, I am finding that the melt function from the reshape library causes errors when applied to a data.frame that contains numeric and character columns. For example, melt(id.vars="ID",data.frame(ID=1:3,date=c("a","b","c"),value=c(1,4,5))) ID variable value 1 1 date a 2 2 date b 3 3 date c 4 1 value <NA> 5 2

Hi all, I've searched threads and read up on some ways of doing this but I'm having a hard time to get it to work. Here's my basic problem. I have the following linear mixed model y = Xb+Zu+e where u~N(0,s^2*K) where K is a matrix. I read a thread that basically suggested to decompose Zu into ZPD^(1/2) D^(-1/2)P'u so that (D^(-1/2)P'u)~N(0,s'^2I) but I'm not sure

Working with 5 subset streams from my source data frame, three of them successfully call dcast(), but two fail: jerritt.cast <- dcast(jerritt.melt, site + sampdate ~ param) Aggregation function missing: defaulting to length and winters.cast <- dcast(winters.melt, site + sampdate ~ param) Aggregation function missing: defaulting to length Yet both data frames have the values in their

Dear list, I'm looking for an inverse function of melt(which is in package reshape).Namely, I had a data frame like this (Table1) YEAR VAR1 VAR2 VAR3 1995 7 3 45 1996 5 6 32 1997 6 10 15 I transformed my data by using the melt function and my data was reshaped in the following format: (Table2) YEAR variable

Hi list, I run R on Linux and OSX. On both systems I use R version 2.9.2 (2009-08-24) and reshape version: 0.8.2 (2008-11-04). When I do a melt with na.rm=T on a data frame I get different results on these systems: library(reshape) x <- read.table(textConnection("char trial wn p E10I13D0 4 r E10I13D0 4 a E10I13D0 4 c E10I13D0 4 t E10I13D0 4 i E10I13D0 4 c E10I13D0 4 e E10I13D0

I have a dataset that is based on crop output for a single crop *sugarcane*...but each observation is further subdivided into 3 kinds of sugarcane i have read the file and have also used melt it to sort it on the basis of *crop group* using melt(sugarcane, m=c("Crop_group")) -> canefile this is how it has cast the data variable value 1 Crop_group Sugarcane