similar to: plot zoo custom panel help

#I would like to use the below data to make a scatter plot matrix with #code similar to that below the data #conceptually this is the right approach I think #thanks in advance melt.gg <- structure(list(stream = c("Bonham Lower", "Bonham Lower", "Bonham Lower", "Bonham Lower", "Bonham Lower", "Bonham Lower", "Bonham Lower",

Hello everyone! I´ve started using R last week and I´m having really persistent problems trying to make predictions using the HoltWinters function. I´m sending my script and the errors I´m getting. My data is: Jan Feb Mar Apr May Jun Jul Ago Sep Oct Nov Dec 2004 118 143 169 158 143 135 135 140 135 125.0000 120.0000 120.0000 2005 143 158 180 180 150 150 153 148 150 145.0000

"[<-" in R 0.63 does not appear to strip attributes, whereas Splus and previous versions of R did. Paul _____ R 0.63: > data <- matrix(rnorm(300),100,3) > attr(data, "tframe") <- c(1981.50, 2006.25 , 4.00) > attributes(data) $dim [1] 100 3 $tframe [1] 1981.50 2006.25 4.00 > z <- data[10:90,] > attributes(z) $dim [1] 81 3 $tframe [1]

Hello Running R2.9.2 on Windows XP I am puzzled by the performance of LME in situations where there are missing data. As I understand it, one of the strengths of this sort of model is how well it deals with missing data, yet lme requires nonmissing data. Thus, m1.mod1 <- lme(fixed = math_1 ~ I(year-2007.5)*TFC_, data = long, random =

Good afternoon Using R 2.9.2 on a machine running Windows XP I have a longitudinal data set, with data on schools and their test scores over a four year period. I have centered year, and run the following m1.mod1 <- lme(fixed = math_1 ~ I(year-2007.5)*TFC_, data = long, random = ~I(year-2007.5)|schoolnum, na.action = "na.omit") where

I have a class "tframe" with more specific classes indicating how time is being represented, such as > class(tframe(data)) [1] "ts" "tframe" but now "[.ts" produces warning messages > tframe(data)[2] Warning: Not returning a time series object [1] 2006.25 Even my simplest tests produce hundreds of lines of warnings, so I've commented out

Dear Helpers, I am looking for methods and tools to compare and then to concatenate two successive time series. They are both in the same frequency and they describe one phenomena. There is no time gap between them. The problem is that the method of measurements has changed between both time series and they are no statistically the same. I would like to merge them to receive one homogeneous

Hello, I apologize in advance as this example seems really elementary. Below I have created a simple scatterplot with lines. I would like to label each line with the name of the village, instead of using a legend. Can someone please let me know how to do it. Thanks in advance -- John Pop=c(1406,1862,2333,2664,2685,2521,2726,0,0,0,0,214,289,365,900,952,1002,1205,1041,942,1004,

On 11-Dec-97 maechler@stat.math.ethz.ch wrote: >>>>>> "PaulG" == Paul Gilbert <pgilbert@bank-banque-canada.ca> writes: > > PaulG> I have a class "tframe" with more specific classes indicating > PaulG> how time is being represented, such as > > >> class(tframe(data)) > PaulG> [1] "ts"