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I have a dataframe of animal locations that I need to have in incremental order so that I can calculate the distance traveled between each time step. However, I have identified a few values that don't seem to sort properly. For instance, the last value in the table below should be the first value after sorting, since its time value is '00:01:35'. But, for some reason, it seems to be

Good morning, I hope someone can help with these questions, or perhaps suggest one of the other R-lists? I have two questions: 1. Why am I getting this warning? 2. Why is the second example "Point Forecast" the same value, I do not see that in previous attempts with similar but different data sets as in example 1? Example1: dat3 <- structure(c(3539122.86, 3081383.87,

My guess would be that if you inspect the output from ma(dat3[1:28], order=3) you will find some NAs in it. And then forecast() doesn't like NAs. But I can't check, because I can't find the ma() and forecast() functions. I assume they come from some package you installed; it would be helpful to say which package. -Don -- Don MacQueen Lawrence Livermore National Laboratory 7000

Hi again. Perhaps a simple question this time.... I am analysing data with a dependent variable of insect counts, a fixed effect of site and two random effects, day, which is the same set of 10 days for each site, and then transect, which is nested within site (5 each). I am trying to fit the cross classified model using GLMM in lme4. I have, for potential use, created a second coding

hi... i am a phd student using r. i am having difficulty plotting average effects. admittedly, i am not really understanding what each of the commands mean so when i get the error i am not sure where the issue is. here is my code... i will include the points at which there are errors.... > dat2 <- dat3 <- dat > dat2$popc100 <- dat2$popc100 + 1000 >

Can somebody tell me that, if I do some arithmetic calculation over 2 matrices then how the column names and row names are preserved? It seems that, for multiplication, column names and row names of the 2nd matrix are preserved and for additional, there seems not having any explicit rule: > set.seed(1) > dat1 <- matrix(rnorm(25), 5); colnames(dat1) = rownames(dat1) =

I've been trying with no success to model mixtures of Gamma distributions using the package flexmix (see examples below). Can anyone help me get it to model better? Thanks very much. -Ben ## ## Please help me get flexmix to correctly model mixtures of ## Gamma distributions. See examples below. ## library('flexmix') ## ## Plot a histogram of dat and the Gamma mixture model given

Hi, From your example data, dat1<- read.table(text=" id1?? id2?? value a????? b?????? 10 c????? d??????? 11 b???? a???????? 10 c????? e???????? 12 ",sep="",header=TRUE,stringsAsFactors=FALSE) #it is easier to get the output you wanted dat1[!duplicated(dat1$value),] #? id1 id2 value #1?? a?? b??? 10 #2?? c?? d??? 11 #4?? c?? e??? 12 But, if you have cases like the one

Hi, Try: dat2<- read.csv("BOlValues.csv",header=TRUE,sep="\t",row.names=1) dim(dat2) #[1] 20 28 indx2<-expand.grid(names(dat2),names(dat2),stringsAsFactors=FALSE) nrow(indx2) #[1] 784 indx2New<- indx2[indx2[,1]!=indx2[,2],] nrow(indx2New) #[1] 756 res2<-sapply(seq_len(nrow(indx2New)),function(i) {x1<- indx2New[i,];

Ira, obj_name<- load("arun.RData") Pred1<- get(obj_name[1]) Actual1<- get(obj_name[2]) dat2<- data.frame(S1=rep(Pred1[,1],ncol(Pred1)-1),variable=rep(colnames(Pred1)[-1],each=nrow(Pred1)),Predict=unlist(Pred1[,-1],use.names=FALSE),Actual=unlist(Actual1[,-1],use.names=FALSE),stringsAsFactors=FALSE) dat2New<- dat2[!(is.na(dat2$Predict)|is.na(dat2$Actual)),] ?dat3<-

Hi all Say I have a function: myname=function(dat,x=5,y=6){ res<<-x+y-dat } for various input such as myname(dat1) myname(dat2) myname(dat3) myname(dat4) myname(dat5) how should I modify the 'res' line, to have new informative variable name correspondingly, such as dat1.res dat2.res dat3.res dat4.res dat5.res stored in the workspace. This is only an example of a complex

HI, You can do this in many ways: dat1<-read.table(text=" med1,med2,med3???? ?1,0,1?????? 0,1,1??? 2,0,0 ",sep=",",header=TRUE)?? #1st method library(reshape) dat2<-melt(dat1) dat3<-aggregate(dat2$value,by=list(dat2$variable),sum) ?colnames(dat3)<-c("name","sum(n11)") ?dat3 #? name sum(n11) #1 med1??????? 3 #2 med2??????? 1 #3 med3??????? 2

Dear Everybody: I'm doing my usual "how does that work in R" thing with some Stata projects. I find a gross gap between the Stata and R in Cox PH models, and I hope you can give me some pointers about what goes wrong. I'm getting signals from R/Survival that the model just can't be estimated, but Stata spits out numbers just fine. I wonder if I should specify initial

In an effort to select the most appropriate number of clusters in a mixture analysis I am comparing the expected and actual membership of individuals in various clusters using the Fisher?s exact test. I aim for the model with the lowest possible p-value, but I frequently get p-values below 2.2e-16 and therefore does not get exact p-values with standard Fisher?s exact tests in R. Does anybody know

Hi List, I'm hoping to get opinions for enhancing the efficiency of the following code designed to take a vector of probabilities (outcomes) and calculate a union of the probability space. As part of the union calculation, combn() must be used, which returns a matrix, and the parallelized version of lapply() provided in the multicore package requires a list. I've found that

Hi all, I have a data matrix likein "input.txt" 8 9 2 5 4 5 8 5 6 6 8 9 2 8 9 2 8 9 2 1 8 9 2 5 4 5 8 5 6 4 8 9 2 5 4 5 8 5 6 6 8 9 2 8 9 2 8 9 2 1 8 9 2 5 4 5 8 9 2 2 In this example will be an 6x10 matrix (or data frame) I want to detect how many times in a row appears this combination 8 follewd by 9 followed by 2, and create a new matrix with only this number of occurs then

Hi, May be you can try this: dat1New<-? dat1[!(duplicated(dat1$gene)|duplicated(dat1$gene,fromLast=TRUE)),] dat2<-dat1[duplicated(dat1$gene)|duplicated(dat1$gene,fromLast=TRUE),] ?lst1<-split(dat2,dat2$gene) dat3<-unsplit(lapply(lst1,function(x) {x1<- sum(apply(x[,6:32],2,function(y) y[1]>=y[2]));x2<- sum(apply(x[,6:32],2, function(y) y[1]<=y[2])); if(x1>x2) x[1,] else

Dear All I am trying to graph a proportion and CI95% by a factor with ooplot (any other better solution ?) It works well until I try to add the confidence interval. this is the error message and and a description of the data: > dat1 PointEst TT1 1 3.6 TT2 2 5.0 TT3 3 5.8 TT4 4 11.5 TT5 5 7.5 TT5 6 8.7 TT7 7 17.4 > dat2

Well, here is one way but it seems a bit clumsy. In words, I created a new data.frame with "250" in the Chloride vector and "SMCL" in the Detections vector and supplessed one legend. Warning: For my convenience I am using different data.frame names . library(ggplot2) MyData <-read.csv("http://doylesdartden.com/Stats/TimeSeriesExample.csv", sep=",")

Hi, I am using mgcv:gam and have developed a model with 5 smoothed predictors and one factor. gam1 <- gam(log.sp~ s(Spr.precip,bs="ts") + s(Win.precip,bs="ts") + s( Spr.Tmin,bs="ts") + s(P.sum.Tmin,bs="ts") + s( Win.Tmax,bs="ts") +factor(site),data=dat3) The total deviance explained = 70.4%. I would like to extract the variance explained