similar to: Strange behaviour when using diff with POSIXt and POSIXlt objects

Dear list, I´m using the mgcv package to model the proportion by weight of certain prey on the stomach content of a predator. This proportion is the ratio of two weights (prey weight over stomach weight), and ranges between 0 and 1. The variance is low when proportion is close to 0 and 1, and higher at intermediate values. It seems that the best way to go is to model this using the

Greetings listeRs - Given a data frame such as times time1 time2 time3 time4 1 70.408543 48.92378 7.399605 95.93050 2 17.231940 27.48530 82.962916 10.20619 3 20.279220 10.33575 66.209290 30.71846 4 NA 53.31993 12.398237 35.65782 5 9.295965 NA 48.929201 NA 6 63.966518 42.16304 1.777342 NA one can use "transform" to

Dear All,   #I have the following code   Dose<-1000 Tinf <-0.5 INTERVAL <-8 TIME8 <-matrix(c((0*INTERVAL):(1*INTERVAL))) TIME7 <-matrix(c((0*INTERVAL):(2*INTERVAL))) TIME6 <-matrix(c((0*INTERVAL):(3*INTERVAL))) TIME5 <-matrix(c((0*INTERVAL):(4*INTERVAL))) TIME4 <-matrix(c((0*INTERVAL):(5*INTERVAL))) TIME3 <-matrix(c((0*INTERVAL):(6*INTERVAL))) TIME2

Hello fellow R's, I?ve been learning to use the ggplot2 library, and after a full day of work I still have a couple of basic questions. Here is an example: mydata=data.frame(x=runif(20),y=runif(20),n=runif(20)) mydata2=data.frame(x=c(0.4,0.6,0.5),y=c(0.4,0.4,0.6)) ggplot(mydata, aes(x, y)) + geom_point(aes(size = n)) + geom_polygon(data=mydata2,aes(x,y,alpha=0.5)) In this plot, the

Dear R folk, First off I want to thank those of you who responded with comments for my R quick and dirty stats tutorial. They've been quite helpful, and I'm in the process of revising them. When it comes to repeated measures MANOVA, I'm in a bit of a bind, however. I'm beginning to see that all of the documentation is written for psychologists, who have a slightly

Hi! I try to explain the efffect of (1) forest where i took samples's soils (* Lugar*: categorical variable with three levels), (2) nitrogen addition treatments (*Tra*: categorical variable with two levels) on total carbon concentration's soil samples (*C: *continue* *variable) during four months of sampling (*Time:* categorical and ordered variable with four levels). I fitted the

Dear R people, I wonder if you could give me a hand with some of my data. I have a very typical analysis in biology, however it is difficult for me to find the right way to analyse. I had a group of animals, I gave them a treatment, and I measure a variable along time -one??s per day- along 5 days,for example(fake data): Animals Time1 Time2 Time3 Time4 1 1 5 3

I am trying to plot where data points from a give subject are connected by a line. Each subject is represented by a single row of data. Each subject can have up to five observations. The first five columns of mydata give the time of observation, columns 6-10 give the values at each time point. Some subjects have all data, some are missing values. The code I wrote to draw the plot is listed below.

I have 100+ .csv files which have the basic format: > test X Substance1 Substance2 Substance3 Substance4 Substance5 1 Time1 10 0 0 0 0 2 Time2 9 5 0 0 0 3 Time3 8 10 1 0 0 4 Time4 7 20 2 1 0 5 Time5

Dear list-members I am new to R and a statistics beginner. I really like the ease with which I can extract and manipulate data in R, and would like to use it primarily. I've been learning by checking analyses that have already been run in SAS. In an experiment with Y being a response variable, and group a 2-level between-subject factor, and time a 5-level within-subject factor. 2

Dear R Masters, I'm an anesthesiology resident trying to make his way through basic statistics. Recently I have been confronted with longitudinal data in a treatment vs. control analysis. My dataframe is in the form of: subj | group | baseline | time | outcome (long) or subj | group | baseline | time1 |...| time6 | (wide) The measured variable is a continuous one. The null hypothesis in

I have included data at the bottom of this email. It can be read in by highlighting the data and then using this command: dat <- read.table("clipboard", header = TRUE,sep="\t") I can obtain solutions with both of these: library(gee) fit.gee<-gee(score ~ chem + time, id=id, family=gaussian,corstr="exchangeable",data=dat) and library(yags) fit.yags <-

Hi, I am having difficulty understanding some lme output -- I haven't found too many examples to help explain to me how to interpret the coefficients and would appreciate any help. I am fitting a model: fit <- lme(y ~ pre + group + time + group:time, random=~1|subject, na.action=na.omit, data=mydata) ...for a dataset where there are two groups being followed over time. pre is

Hi, I have a problem. I have a data frame looking like: ID val A? .3 B? 1.2 C? 3.4 D? 2.2 E? 2.0 I need to CREATE the following TABLE: CASE?? DIFF A-A??? 0 A-B??? -0.9 A-C??? -3.1 A-D??? -1.9 A-E??? -1.7 B-A??? ... B-B??? ... B-C B-D B-E C-A C-B C-C C-D C-E D-A D-B D-C D-D D-E E-A E-B E-C E-D E-E WHERE CASE IS THE COUPLE OF ELEMENTS CONSIDEREDM AND DIFF IS THE computed DIFFERENCE between

Dear list, I?m wondering if there is something analogous to the TukeyHSD function that could be used for parametric terms in a GAM. I?m using the mgcv package to fit models that have some continuous predictors (modeled as smooth terms) and a single categorical predictor. I would like to do post hoc test on the categorical predictor in the models where it is significant. Any suggestions?

Dear list, I?m having a little trouble with adding vertical lines to a histogram. I need to draw a matrix of histograms (using facets), and in each histogram add a vertical line indicating the mean value of the data in each facet. According to the last example in the geom_hline help, to display different lines in each facet I need to provide a data frame. I modified this example to make a plot

Hello I have some strange output from R and I try to understand how R works. Could you please help me with that? temp <- rbind (c(10,1),c(99,98)) > temp [,1] [,2] [1,] 10 1 [2,] 99 98 > dist(temp) 1 2 131.6435 > sqrt(dist(temp)) 1 2 11.47360 so far so good. until the nex line: when I try to do what i did before but adding the 1/(what I did

Hello, Below is the code for a basic bar graph. I was seeking advice regarding the following: (a) For each time period there are values from 16 people. How I can change the colour value so that each person has a different colour, which recurs across each of the three graphs/tie epriods? (b) I have seen much more sophisticated examples using lattice (e.g each person has a separate

Dear all, I am a new user of R. I would like to know how to get fund's returns in percentage (%). For example, I use: R <- ts(read.xls("FundData"), frequency = 12, start = c(1996, 1)) Whith this program, the returns are like 0.0152699. But, I would like to have 1.52%. Please advise me about the function. Thanks! Fabrice

Hello, I am trying to find a direct way to write a nested if of sorts to find data for a specific time range for a specific day (across a range of days) and have exhausted my abilities with the manuals I have at hand. I have a good deal of data of this approximate form: day time price 1 1am 5 1 2am 7 1 3am 9 1 4am 12 2 1am 5 2 2am 7 2