similar to: repeated measures

Hi all I can't find what I am looking for so I am asking here. I have a dataset that looks something like this. Year season percent_below 2000 Winter 6.9179870 2000 Spring 1.6829436 2000 Summer 1.8463501 2000 Autumn 3.8184993 2001 Winter 2.8832806 2001 Spring 2.5870511 2001 Summer 0.0000000 2001 Autumn 4.7248240 2002 Winter

Hi, I'm from Italy (sorry for my english...). I've two questions about the plot function. I've to create a simple graph for the data set "n_species": species=sqlQuery(dati, "select count(distinct species), season from captures_complete_r group by species, season") n_species=tapply(species$count, species$season, sum) n_species=data.frame(n_species) n_species

Dear R-help, My dataset (which is a data frame, called 'Calender' here) includes 365 rows representing 365 days for a year. One column ('Season')contains factor data representing seasons, e.g. spring, summer, autumn and winter. Another column (called 'Day') contains data representing wether the day is a working day (I use 'Wd' for short here)or weekend (I use

Dear all, I'm not very sure on the use of repeated measures in R, so some advice would be very appreciate. Here is a simple example similar to my real problem (R 2.6.0 for windows): Lets supose I have annual tree production measured in 9 trees during 3 years; the 9 trees are located in 3 different mountains (sites), and each tree receive different annual rainfall (different locations). I would

Does anyone know of a way of dealing with unbalanced mixed effects (fixed and random factors) for fully factorial designs. An example of such data is given below; The response variable is SQRTRECRUITS SEASON is a random factor DENSITY is a fixed factor Thus DENSITY:SEASON is a fixed factor. Therefore, whereas the effects of SEASON and DENSITY:SEASON should be tested against the overall

Dear R users, I am currently working in subsetting a zooreg() object using either window or subset. I have a solution but it may be a bit cumbersome when I start working with actual data. Your inputs would be greatly appreciated. Example: I have a zooreg() object that starts in 1997 and ends in 2001. This object contains daily data for the 4 years

Hello everybody, I need to calculate seasonal means with temperature data for my work. I have 70 files coming from weather stations, which looks like this for example: startdate <- as.POSIXct("01/01/2006", format = "%d/%m/%Y") enddate <- as.POSIXct("05/01/2006", format = "%d/%m/%Y") date <- seq(from = startdate, to = enddate, by =

Dear all, How can I run a constrained correspondence analysis with the following data: 15 animals were measured repeatedly month-wise (over to 2 years) according to ther diet composition (8 food categories). our data.frame looks like this: food 1 2 ... 8 sex season year animal freq 12 8 ... 1 0 summer 2011 1 freq 0 7 ... 0 1 winter 2011 1 ... freq 0 7 ... 0 1 spring 2011 15 We

Dear all, I am using RDA to study plant communities in various land uses (variable LU with values M, U, etc.). For each land use, I sample 3 to 5 fields (M1, M2, U1, U2, etc). I make 5 measurements for both plant communities and environmental variables in each field. I repeat the process every 6 months to study the effect of time and season (D16 for dry season 2017, R16 for rainy season 2016,

I want to obtain a barplot with error bars and a mean plot with error bars with other scale on the left in the same plot. I need help to get the same x axis (centered) when overlay two plots (barplot2 and plotCI (or lineplot.CI) with errorbars), with diferent y axis. I use par (new=T) but the X axis names are not centered with the figures. An example of my data:

Hi Irucka, No problem. I guess this could be done using: Sample data: Dailydo<- structure(list(Date = structure(c(11231, 11232, 11233, 11234, 11235, 11236, 11207, 11208, 11209, 11179, 11180, 11181, 11151, 11152, 11123, 11093, 11064, 11065, 11035, 11036, 11008, 11009, 10979, 10980, 11347, 11348, 11380, 11381, 11410, 11406, 11438, 11439, 11470, 11502, 11528, 11560, 11561, 11593, 11594,

I am trying to make predictions with se's using a nlme (kew11.nlme below). I get an error indicating levels for a factor are not allowed. I have searched and read Rnews, MEMSS, MASS, R-Help, and other lists in Spanish where I found questions similar to mine but not solution. I do not really care about the method used. Any suggestions to obtain predictions with se's from an nlme

Dear Gavin, This is really great, thank you! I created some long loops to get rid of extra months at the beginning and the end of my data but your code is great for putting it then together quarterly. thanks again, Denise On Mon, 2008-08-18 at 14:31 +0100, Denise Xifara wrote: > Thank you very much Stephen, but how will aggregate deal with months that > fall outside annual quarters? eg,

Hi, This is actually a theory question. I'm a bit confused by the s.window parameter in the stl() function (which is in the ts package). For example, in the stl documentation it uses the nottem data, and then: plot(stl(nottem, s.win = 4, t.win = 50, t.jump = 1)) What does it mean by s.win = 4? Is it because a year has 4 seasons (namely Spring, Summer, Autumn and Winter)? If so will it

In the autumn and winter it's considered bad form to set power state to D3cold, it might cause the device to freeze to death. This is also the case in the other seasons, so any device in the southern hemisphere is affected too. D3cold is not a valid state in a call to pci_set_power_state, only up to D3hot is allowed. Signed-off-by: Maarten Lankhorst <maarten.lankhorst at canonical.com>

Hi , I know this question has been asked twice in the past but to my knowldege, it still hasn't been solved. I am doing a zero inflated binomial model using the VGAM package, I need to obtain p values for my Tvalues in the vglm output. code is as follows > mod2=vglm(dmat~Season+Diel+Tidal.phase+Tidal.cycle,zibinomial, data=mp1) > summary(mod2) Call: vglm(formula = dmat ~ Season +

Hello all, I cannot seem to figure out this seemingly simple procedure. I want to sort a data frame by a specified character vector. So for : df.. <- data.frame(Season=rep(c("Summer","Fall","Winter","Spring"),4),Obs= runif(length(rep(c("Summer","Fall","Winter","Spring"),4)))) I want to sort the data frame

Dear all, I have got two vectors coding for a stimulus presented in the current trial (mydat$Stimulus) and a prediction in the same trial (mydat$Prediciton), respectively. By applying an if-conditional I want to create a new vector that indicates if there is a match between both vectors in the same trial. That is, if the prediction equals the stimulus. When I pick out some trials randomly, I get

Hi R users Here is an example of my data (only a small part) Year Season A_Time R_Time O_Time All_Time AandR_Time A_number R_number O_number AandR_number all_number 1999 Winter 9.590741 35.312963 42.759524 23.228431 18.164815 18 9 7 27 34 2000 Winter 9.899537 47.945000 59.744444 20.301333 18.170290 36 10 3

> Hi R users > Here is an example of my data (only a small part) > > Year Season A_Time R_Time O_Time All_Time AandR_Time > A_number R_number O_number AandR_number all_number > 1999 Winter 9.590741 35.312963 42.759524 23.228431 18.164815 > 18 9 7 27 > 34 > 2000 Winter 9.899537 47.945000 59.744444 20.301333