search for: tdata

Hi All, I am attempting to work with some data from loggers. I have read in a .csv exported from MS Access that already has my dates and times (in 24 clock format), (with StringsAsFactors=FALSE). > head(tdata) LogData date time 1 77.16 2008/04/24 02:00 2 61.78 2008/04/24 04:00 3 75.44 2008/04/24 06:00 4 89.43 2008/04/24 08:00 5 95.83 2008/04/24 10:00 6 96.88 2008/04/24 24:00 I wish to be able to summarise the data...

...k on my system. Please advise regarding options that must be specified to "plot(summary(", or in the construction of my loop. Below are sample code and my sessionInfo(). Please note that I am using data.table to facilitate my "real analysis", but I can replicate the issue with tData as a data.frame (using seg <- subset(tData, groups == segment) logic), but I included the data.table logic in case it may be having some influence. Thank you! Mike tData <- data.frame(groups=as.factor(1:8), low=as.factor(1:4) ,high=as.factor(seq(100, 400, 100)), rand=runif(400)) tData &...

Dear Group, I have the following data matrix which is a timeseries. > dput(tData) structure(list(A = c(0.2, 0.13, 0.05, 0.1, 0.02, 0.18, 0.09, 0.06, 0.13), B = c(0.15, 0.06, 0.09, 0.02, 0.03, 0.12, 0.01, 0.15, 0.06), C = c(-0.1, 0, -0.07, -0.06, -0.05, -0.05, -0.06, -0.08, -0.07), D = c(-0.15, -0.05, -0.1, -0.03, -0.13, -0.04, -0.1, -0.04, -0.15), E = c(-0.17, -0.16, -0.08,...

...ata=data.frame("y"=x[,1]*10,"x"=x[,2]))) summary(vglm("y~x",family=hypersecant,data=data.frame("y"=x[,1],"x"=x[,2]))) summary(vglm("y~x",family=hypersecant,data=data.frame("y"=x[,1]*10,"x"=x[,2]))) *Ex 2* library(VGAM) tdata <- data.frame(x2 = runif(nn <- 1000)) tdata <- transform(tdata, y1 = rt(nn, df = exp(exp(0.5 - x2))), y2 = rt(nn, df = exp(exp(0.5 - x2)))) fit1 <- vglm(y1 ~ x2, studentt, tdata, trace = TRUE) tdata$y1=tdata$y1*100 fit2 <- vglm(y1 ~ x2, studentt, tdata, trac...

...s.data.frame(z) if(dim(z)[2] == 0){ stop("There should be given data\n") } data <- data.frame(x,y,z) if(na.rm == T){ data = na.omit(data) } - Ignored: # recursive formula if(dim(z)[2] == 1){ tdata <- na.omit(data.frame(data[,1],data[,2])) rxy <- cor(tdata[,1],tdata[,2],m=method) tdata <- na.omit(data.frame(data[,1],data[,-c(1,2)])) rxz <- cor(tdata[,1],tdata[,2],m=method) tdata <- na.omit(data.frame(data[,2],data[,-...

..."incident_type")]), responses=unique(from[,c("incident_num", "unit", "response_time")])) }) ### define methods setMethod("head", "CAD", function(x, n=5, row.names=NULL, optional=FALSE, ...){ tdata = merge(x@responses, x@incidents, by="incident_num", all.x=TRUE) head(tdata, n=n, row.names=row.names, optional=optional) }) setMethod("tail", "CAD", function(x, n=5, row.names=NULL, optional=FALSE, ...){ tdata = merge(x@respons...

...tely then piece them back together into one document.. Thanks in Advance for any help! options (scipen=999, digits=7) library(foreign) library(Hmisc) library(prettyR) library(DAAG) library(lmtest) library(car) library(MASS) library(nlme) library(dyn) library(wle) library(lasso2) library(zoo) tdata <- ts(read.table("C:/tmp/data.csv" ,sep = ",",header=TRUE)) print(tdata) res <- function(dep, indep, fn, env = parent.frame()) { depnm <- deparse(substitute(dep)) indepnm <- deparse(substitute(indep)) fo <- sprintf("%s ~ lag(%s, -1) +...

...rmula = dyn(Y ~ lag(Y, -1) + XVARY)) -----> this is what I want to see (see simplified version of the code and output below) Thanks in advance for any help!! options (scipen=999, digits=7) library(Hmisc) library(DAAG) library(car) library(MASS) library(nlme) library(dyn) library(zoo) tdata <- ts(read.table("C:/R/testing/data.csv" ,sep = ",",header=TRUE)) print(tdata) coeff <- function(dep, indep) { mod <- dyn$lm(dep ~ lag(dep, -1)+ indep) summ <- summary(mod) res <- list(COEF=summ) } out <- coeff(tdata[ ,"Y"], td...

...mes?). So when i run HEAD(DATAFRAMENAME) i get the column name = "Open". but you can see below... it is called "newcol2 with some attribute called open. I did a lot of google searches but really could not find what i was looking for. Any help is greatly appreciated. Thank you! tdata[["newcol2"]] <- rbind(0,apply(tdata["Open"],2,diff)) > str(tdata) 'data.frame': 7505 obs. of 8 variables: $ Date : int 19860709 19860710 19860711 19860714 19860715 19860716 19860717 19860718 19860721 19860722 ... $ Open : num 9.14 9.45 9.3 9.08 8.71 ......

Hi all, I have been previously been using scatterplot3d package to create some graphs but unfortunately it does not allow me to rotate the plot on all three axis. The cloud() function in the lattice package does allow me to do so. When I was using scatterplot3d I was using a script (Shown Below) to calculate the mean, quartiles and range limits for all three axis and I was representing that on the

I don't normally have to go anywhere near this stuff , but it seems to me that this should be a straight-forward process in R. For the purposes of this enquiry I thought I would use something I can work out on my own. So I have my matrix and the right hand results from that matrix tdata <- matrix(c(0,1,0,-1,-1,2,0,0,-5,-6,0,0,3,-5,-6,1,-1,-1,0,0),byrow = T,ncol = 5) sumtd <- c(0,0,0,-2) > tdata [,1] [,2] [,3] [,4] [,5] [1,] 0 1 0 -1 -1 [2,] 2 0 0 -5 -6 [3,] 0 0 3 -5 -6 [4,] 1 -1 -1 0 0 > sumtd [1] 0 0 0 -2 &g...

Hi, I have been trying draw tickmark labels along the y - axis perpendicular to the y axis while labels along the x - axis parallel to x axis while making box plot. Here is my test dataset. TData ID Ratio 1 0 7.075 2 0 7.414 3 0 7.403 4 0 7.168 5 0 6.820 6 0 7.294 7 0 7.238 8 0 7.938 9 1 7.708 10 1 8.691 11 1 8.714 12 1 8.066 13 1 8.949 14 1 8.590 15 1 8.714 16 1 8.601 boxplot(Ratio ~ ID, data=TData) makes box plot with tickmark labels parallel to the y - axis...

...an example that does not use the survival library. # first create a data set with many long names n <- 30? # number of rows for the dummy data set vname <- vector("character", 26) for (i in 1:26) vname[i] <- paste(rep(letters[1:i],2), collapse='')? # long variable names tdata <- data.frame(y=1:n, matrix(runif(n*26), nrow=n)) names(tdata) <- c('y', vname) # Use it in a formula myform <- paste("y ~ cbind(", paste(vname, collapse=", "), ")") mf <- model.frame(formula(myform), data=tdata) match(attr(terms(mf), "term.l...

Dear all, ?The code below is used to generate interval censored data but unfortunately there is an error with the ifelse which i am not able to rectify. ?Can somebody help correct it for me. Thank you t<-rexp(20,0.2)? v<-c(0,m,999)? y<-function(t,v){ ? z<-numeric(length(t (( ? ? s<-numeric(length(t (( ? ? ? for(i in 1:length(t)){ ? ? ? ? for(j in 1:length(v-1))? ? ? ? ? { ifelse

...seqnames = rep(i,nrow(mp)), ranges = IRanges(start = mp[[1]], end = mp[[1]]+(mp[,2]-1)), strand = rep("+", nrow(mp))) #OL <- findOverlaps(query=gr, subject=annotGr) OL.p <- annotGr[(!is.na(match(annotGr, gr)))] #as.data.frame(OL) ## view the results #tdata.p <- annotGr[unique(queryHits(OL)),] #tdata.p <- as.data.frame(tdata.p, row.names = NULL, optional = FALSE) #write.table(tdata.p, paste(i,"plus.txt")) cat( paste(i,"plus.txt\n")) } OL.m <- NULL if(nrow(mm) > 0) { ##### MATCH THE MINU...

Hi, All, This is my program ts1.sim <- arima.sim(list(order = c(1,1,0), ar = c(0.7)), n = 200) ts2.sim <- arima.sim(list(order = c(1,1,0), ar = c(0.5)), n = 200) tdata<-ts(c(ts1.sim[-1],ts2.sim[-1])) tre<-c(rep(0,200),rep(1,200)) gender<-rbinom(400,1,.5) x<-matrix(0,2,400) x[1,]<-tre x[2,]<-gender fit <- arima(tdata, c(1, 1, 0), method = "CSS",xreg=t(x)) I try to fit a ARIMA model and aclude some other independent variable in t...

I have tData as below. I need to set the names with the headers from the first row in sHeaders Sorry .. forgot how to set the names from row in another data frame .. pls advise. names(tData) = sHeaders[1,] does not work correctly Also, why doesn't drop.levels(sHeaders) not work? dput(tData) structure(li...

Hola a todos Estoy intentando hacer un análisis rápido de una serie temporal de datos diarios pero me encuentro con algunos problemas. Me gustaría en primera instancia hacer una regresión lineal pero no encuentro la forma. Tras leer los datos diarios creo un objeto de la clase zoo y sobre éste no puedo utilizar lm(). He leído algo sobre dynlm pero no encuentro la forma. Se agradece

Consider the following simple data set and a call to ave: > tdata <- data.frame(f1=c(1,1,1,1,2,2,2,2), f2=c(1,2,1,2,1,1,1,1), y=1:8) > with(tdata, table(f1, f2)) f2 f1 1 2 1 2 2 2 4 0 > with(tdata, ave(y, f1, f2, FUN=max)) [1] 3 4 3 4 8 8 8 8 Warning message: In FUN(X[[i]], ...) : no non-missing arguments to max; returning -Inf There are...

...better. This seems odd. This issue is meaningful since the output of this regression needs to be implemented in a production system, and mboost doesn't even expose the ensembles. # default params for blackboost are a gaussian loss, and maxdepth of 2 m.mboost = blackboost(Y ~ X1 + X2, data=tdata, weights=t.ipcw, control=boost_control(mstop=100)) m.gbm = gbm(Y ~ X1 + X2, data=tdata, weights=t.ipcw, distribution="gaussian", interaction.depth=2, bag.fraction=1, n.trees=2500) # compare IPCW weighted squared loss sum((predict(m.mboost, newdata=tdata)-tdata$Y)^2 * t.ipcw) < sum((pr...