similar to: S 3 generic method consistency warning please help

Hello, I am getting output from anova() and summary(aov()) that depends on the order of the factors in the fitted model object, and this has me baffled. I see this dependency with the data.frame below but not with an example (table 6.4) from Montgomery's DOE book. This is with R 1.3.0 on Debian GNU-Linux. Where have I gone wrong? > centerpts run sample CH50mg 1 day1 dev126 0.56 2

Hi, I have a data.frame SAMPLES with columns: Site Site# Season Day1 Day2 Day3 Day1, Day2, Day3 are class "Date", the other columns are numeric or factor. I have a date "mydate" that may or may not be listed in my data.frame and I need to find that out. If "mydate" is there, I want to get the number of the data.frame row where it occurs.

thanks to your guys help I am closer to solving my problem but I have some small problem. So let's say I start with >data number day hour 1 17 10 2 17 11 3 17 6 4 18 4 5 18 10 6 19 8 7 19 8 I want to split to odd days, which I am able to do, I call this object frames, which looks like: > frames $`1` c1 day1 hour1 1 1 17 10 2 2 17 11 3 3 17 6 $`2` c1 day1

I have a series of tables, one for each environment indicating a date (row) and a sample at each hour of the day (0 to 23) Test1 Table: Date,Hour1,Hour2,...Hour23 1/1/10,123,123,...,123 I would like to model this as a time series but how can I translate the table into a list such that I can get: 1/1/10 00:00, 123 1/1/10 01:00, 123 1/1/10 02:00, 123 ... 1/1/10 23:00, 123 Any suggestions on how

HI all, raw_urine = read.table("Z:\\bruce.9.3.09.sample.stability.analysis\\urine\\mz.spot.sam.dat.new", header = TRUE ) pvalue = read.table("Z:\\bruce.9.3.09.sample.stability.analysis\\urine\\all.urine.features.t.test.result", header = TRUE ) library(compositions) p = function(a,b){ y = pvalue[,a] if(y<0.01){ index = which(y, arr.ind=TRUE) day1 = raw_urine[index,3:7] day2 =

Dear group, Here is my environment : > ls() [1] "l" "PLglobal" "Pos100415" "Pos100416" "Pos100419" "Pos100420" "position" "select" "Trad100415" "Trad100416" "Trad100419" "Trad100420" "trade" "y" With objects : > l [1]

I have the following function defined as below match.trace <- function(dfobj, distance, day1, day2) { day1 <- substitute(dfobj$day1); day1 day2 <- substitute(dfobj$day2) distance <- substitute(dfobj$distance) xx <- NULL for (i in 0:10) xx[i+1] <- with(dfobj, cor(Lag((day1-day1[1]),i), (day2-day2[1]), use='pair')) i <- match(max(xx), xx) with(dfobj, {

Hi, If I have a data frame A with the following format: Day1 Day2 Day3 Day4 1 1979-11-02 1979-11-03 1979-11-04 <NA> 2 1979-12-06 <NA> <NA> <NA> 3 1979-12-13 1979-12-14 1979-12-15 1979-12-16 4 1979-12-20 <NA> <NA> <NA> And a date "1979-12-14", for

Dear helpeRs- I'm using a for loop to create a series of models. I'm trying to assign a name to each model created, using the loop index. The loop gets stuck at the name of the model, giving the error "target of assignment expands to non-language object". The linear model runs without error; only the name is problematic. Here is the current loop syntax. The use of dat

Can someone help me with the proper usage of the reshape function? Let's say I have a dataset with columns like this (wide format): Id Sex Group Test Day1 Day 2 Day 3... And I want to transpose this into something like this (thin): Id Sex Group Test Time Where the new column labeled time contains all the time variables (Day 1, Day 2, Day 3...) that were in the wide

I have this problem with records that have to be alligned on end- and startdate. I came up with the following. but am not convinced that this is the best way to tackle this problem. Anyone care for a braindump? def head_to_tail # Remove days that have startdate >= self.startdate AND enddate <= self.enddate # # before after # # |=====| |=====|

Hi, I am an R novice and I am trying to do something that it seems should be fairly simple, but I can't quite figure it out and I must not be using the right words when I search for answers. I have a dataset with a number of individuals and observations for each day (7 possible codes plus missing data) So it looks something like this Individual A, B, C, D Day1 1,1,1,1 Day 2 1,3,4,2 Day3

Dear all, Just wondering if someone could help me out converting my code from a for() loop into a foreach() loop or using one of the apply() function. I have a very large dataset and so I'm hoping to make use of a parallel backend to speed up the processing time. I'm having trouble getting selecting three variables in the dataset to use in the foreach() loops. My for() loop code is:

Dear all, I have the following data in excel: day1 y 1 2 3 2 3 x1 0.2 0.3 0.4 0.3 0.2 x2 7 3.4 2 8 6 day2 y 2 4 3 2 2 x1 0.4 0.5 0.3 0.3 0.2 x2 7 8 9.1 6 5 I have the following problems: first of all, when I ask R to read the file (with the package xlsReadWrite and the command read.xls) it has a problem with the fact that the left most corner is labelled the same way, so in order for it

This patch adds support for symbol versions. It is based on what libvirt does. The generated syms file looks like: LIBNBD_1.0 { global: nbd_...; nbd_...; local: *; }; In a future stable 1.2 release, new symbols would go into a new section which would look like this: LIBNBD_1.2 { global: nbd_new_symbol; nbd_another_new_symbol; local: *; } LIBNBD_1.0; In my testing the

library(zoo) library(chron) t1 <- chron("1/1/2006", "00:00:00") t2 <- chron("1/31/2006", "23:45:00") deltat <- times("00:15:00") tt <- seq(t1, t2, by = times("00:15:00")) d <- sample(33:700, 2976, replace=TRUE) sin.zoo <- zoo(d,tt) #there are ninety six reading in a day d.max <- rollapply(sin.zoo, width=96, FUN=max)

Hi all, I have been bumbling around with r for years now and still havent come up with a solution for plotting reliable graphs of relationships from a linear regression. Here is an example illustrating my problem 1.I do a linear regression as follows summary(lm(n.day13~n.day1+ffemale.yell+fmale.yell+fmale.chroma,data=surv)) which gives some nice sig. results Coefficients:

I am was going to look at the as.yearmon function in the zoo package and write a as.day function to aggregate a time series of 96 observations per day into the mean for each day, but I don't know how to look at the code so that I can convert it into something I can use. On top of that I believe that it is probably an S3 method and I haven't quite gotten that far in my programming

I’m using a Windows development component which uses vorbis.dll, ogg.dll, vorbisenc.dll for encoding an Ogg Vorbis file. It's all working well except for one user occasionally has a 1 hour file appear as 2 hours and it plays at half speed. It is being converted from stereo to mono before feeding the encoder with a channels=1 configuration. Here is an example file which will be available for

Hi, i did a mistake with my first post. I have to reshape data from this matrix: id x1 x2 x3 x4 day1 day2 day3 day4 day5 day6 day7 day8 day9 1 0.129 0.797 0.231 0.615 4 4 1 1 1 1 3 3 3 2 0.420 0.376 0.501 0.282 4 4 4 4 5 4 2 5 5 3 0.377 0.486