similar to: reshaping data

All R experts, How do I fit a dynamic Random effects model with a binary dependent variable in R Thanks JCM [[alternative HTML version deleted]]

Dear R-users, I have a complex line by xy-values (ordered by z). And I would like to get interpolated y-values on the positions of x = 0:600. How do I get the correct points? x=c(790,790,790,790,790,786,783,778,778,766,763,761,761,761,715,628,521,350,160,134,134,129,108,101,93,111,161,249,288,243,139,45,7)

Hello all! I have a problem to extract values greater that for example 1820. I try this code: x[x[,1]>1820,]->x1 Please help me! Thank you! The data structure is: structure(c(2.576, 1.728, 3.434, 2.187, 1.928, 1.886, 1.2425, 1.23, 1.075, 1.1785, 1.186, 1.165, 1.732, 1.517, 1.4095, 1.074, 1.618, 1.677, 1.845, 1.594, 1.6655, 1.1605, 1.425, 1.099, 1.007, 1.1795, 1.3855, 1.4065, 1.138, 1.514,

Hello all! I have a problem with R. I try to merge data like this: structure(c(2.1785, 1.868, 2.1855, 2.5175, 2.025, 2.435, 1.809, 1.628, 1.327, 1.3485, 1.4335, 2.052, 2.2465, 2.151, 1.7945, 1.79, 1.6055, 1.616, 1.633, 1.665, 2.002, 2.152, 1.736, 1.7985, 1.9155, 1.7135, 1.548, 1.568, 1.713, 2.079, 1.875, 2.12, 2.072, 1.906, 1.4645, 1.3025, 1.407, 1.5445, 1.437, 1.463, 1.5235, 1.609, 1.738, 1.478,

Hello all! I have a problem to group my data (years) in 10 years classes. For example for year year decade 1598 1590-1600 1599 1590-1600 1600 1590-1600 1601 1600-1610 --- my is like this> [1] 1598 1599 1600 1601 1602 1603 1604 1605 1606 1607 1608 1609 1610 1611 1612 [16] 1613 1614 1615 1616 1617 1618 1619 1620 1621 1622 1623 1624 1625 1626 1627 [31] 1628 1629 1630 1631 1632 1633

Hi, again i am stuck in my presentation, and i have never learn R before in my life but need this to be done, so please help me out for a favour: http://www.nabble.com/file/p20333155/kew.dat kew.dat run this in R and these comes up: Month Year Rain 1 Jan 1900 74.400000 2 Feb 1900 80.500000 3 Mar 1900 23.600000 4 Apr 1900 23.600000 5 May 1900 25.100000 6

Hi all, I ran a Weibull model, and I am wondering if there is any way to extract the log likelihood. I tried loglik(model) but it does not seem to work any help would be greatly appreciated joe [[alternative HTML version deleted]]

Dear R experts, I am trying to estimate an ARMA 2,2 model with garch errors. I used the following code on R 2.9. #library library(fGarch) #data data1<-ts(read.table("C:/Users/falcon/Desktop/Time Series/exports/goods1.csv"), start=c(1992,1), frequency=12) head(data1) #garch garchFit(formula.mean= ~arma(2,2),formula.var=~garch(1,1), data=data1) but get this error: >

Hi all, can the glm package be used to estimate a logit model to panel data? I am asking this because stata has a standard logit model and then an xtlogit for longitudinal data. Is there something similar in R? Thank you jcm [[alternative HTML version deleted]]

I am trying to extract only the winters (defined to be 01-Dec through 28-Feb) of daily data from 1948-2002. There are 90 days in each winter season. I wrote the following code to gather the winter dates into a single vector: DJF <- NULL for(year in 1949:1999) { temp.begin <- strptime(paste("01/12", year-1, sep="/"), "%d/%m/%Y") temp.end <-

Hello all! I have a problem with my data in R. When I want to plot the following data, I have a problem with y scale. The maximum value is cc. 10 degrees and in R is about 100. I use this code: fasy<-read.table("gridd1.txt",sep="\t",dec=",",header=T,row.names=1) # here are the years: x <- as.numeric(rownames(fasy)) # extract a series that you want to plot: y

I have two collections of dates and I want to figure out what dates they have in common. This is not giving me what I want (I don't know what it is giving me). What is the best way to do this? Tom > data1 [1] "1948-02-24 EST" "1949-04-12 EST" "1950-05-29 EDT" "1951-05-21 EDT" [5] "1951-12-20 EST" "1953-01-22 EST"

Dear Rui and UseRs,[a text file has also been attached, in case the format of my email is difficult to get]I am extremely sorry that I am bothering you once again, but I?ll have to get to the bottom of it. The following command sp <- lapply(split(agg, agg$st), function(x) x[order(x$year, x$month), ]) gave me an output with monthly mean of population(as under). i am not able to apply

I can't seem to find just what I'm looking for in R help, Everitt and Hothorn HSAUR, Murrell's book, or the R graphics gallery at http://addictedtor.free.fr/graphiques/. Probably not looking efficiently, but anyway, If my data look like this: > head(data) cat startyear studentid 1 other 2001 12 2 UHS 2001 17 3 Lourdes 2001 10 4

Hello, i have following problem and I hope you can help me a little bit My dataframe looks like: df a m d typ value 1950 1 1 5 -4.1 1950 1 2 9 2.7 1950 1 3 3 -1.3 1950 1 4 5 -1.9 1950 1 5 2 0.2 1950 1 6 8 0.5 1951 1 1 4 1.3 .... It consists by daily observations from 1950- 2009. Now, I get with.... for (i

Hi, [auto build test ERROR on next-20160602] url: https://github.com/0day-ci/linux/commits/Aaron-Conole/virtio-net-Advised-MTU-feature/20160603-000714 config: i386-allmodconfig (attached as .config) compiler: gcc-6 (Debian 6.1.1-1) 6.1.1 20160430 reproduce: # save the attached .config to linux build tree make ARCH=i386 Note: the

Hi, [auto build test ERROR on next-20160602] url: https://github.com/0day-ci/linux/commits/Aaron-Conole/virtio-net-Advised-MTU-feature/20160603-000714 config: i386-allmodconfig (attached as .config) compiler: gcc-6 (Debian 6.1.1-1) 6.1.1 20160430 reproduce: # save the attached .config to linux build tree make ARCH=i386 Note: the

Hi I am writing a package in which I define a new class in the .onLoad() hook: ,---- | .onLoad <- function(libname, pkgname) { | setClass( | "inDrak", | representation( | init = "SpatialGridDataFrame" | ), | contains = "simObj" | ) | } `---- The class "simObj" is defined in the package, which

I have the following data (see RawData using dput below) How do I get it in the following 3 column format (CO2 measurements are the elements of the original data frame). I'm sure the package reshape is where I should look, but I haven't figured out how. Thanks ahead of time Month Year CO2 J 1958 F 1958 M 1958 315.71 A 1958 317.45 M.1 1958 317.5 J.1 1958 J.2 1958 315.86 A.1 1958

Hi. This may be a straight-forward question... I have a time series from 1950 to 2000 (by year) with missing values. Sometimes only a year has value and the adjacent years have missing data, e.g. 1950 2.7 1951 1952 1953 3.4 1954 1955 1956 2.9 1957 3.6 1958 2.7 When I use plot (type='l'), the line can't connect the 'stand-alone' years. Is there a way I have have R to skip