similar to: barplot with more than 1 variable

I am having a hard time putting the below into a loop, where it pulls out ppt from all he stations I have versus having to go through and hard code the data to the specific stations. I tried stnID <- stnid[which(duplicated(stnid)==FALSE)] for(i in 1:length(stnID)) { ppt[i] <- ppt[which(stnid==[i])] } but it doesn't like to use the which function inside a for loop? Any idea's here is

I need to apply a yearly inflation factor to some wages and supply some simple sums by work category. I have gone at it with a brute force "for" loop approach which seems okay as it is a small dataset. It looks a bit inelegant and given all the warnings in the Intro to R, etc, about using loops I wondered if anyone could suggest something a bit simpler or more efficent? Example:

I would like to know how I can assign a name to a name. I have a dataset that has different years in it. I am writing scripts using R and I would like to give a month a generic name and then use the generic name to do different analysis. The reason for the generic name would be so that I only have to change one thing if I wanted to change the year. For example. Year1 = 1999 datayear <-

The following is my R script which I am struggling with to assess ICESat data..perhaps it is the ID_min or ID_max that is wrong? I don't know, any help would be greatly appreciated :( # OPTIONS - CHANGE THESE VARIABLES IF NEEDED\par ######################################################################\par \par icesatfile <-

I am graphing longitudinal data from three time points. I'd like to draw a solid line from point 1 to point 2, and then a dashed line from point 2 to point 3. It works if I do it in two steps: > first.vector <- c(mean(year1$variable1), mean(year2$variable1)) > second.vector <- c(NA, mean(year2$variable1), mean(year3$variable1)) > plot(first.vector, type="b",

Dear R Helpers I have following data - cash_flow = c(7, 7, 107)  # 107 = Principle 100 + interest of 7% t = c(1,2,3) and zero rate table as rating         year1           year2           year3 AAA            3.60            4.17              4.73 AA              3.65            4.22              4.78 A                 3.72           4.32              4.93 BBB            4.10           

Hi R-helpers, My real data is a panel (unbalanced and with gaps in years) of thousands of firms, by year and industry, and with financial information (variables X, Y, Z, for example), the number of firms by year and industry is not always equal, the number of years by industry is not always equal. #reproducible example firm1<-sort(rep(1:10,5),decreasing=F) year1<-rep(2000:2004,10)

I R-helpers #I have a data panel of thousands of firms, by year and industry and #one dummy variable that separates the firms in two categories: 1 if the firm have an auditor; 0 if not #and another variable the represents the firm dimension (total assets in thousand of euros) #I need to create two separated samples with the same number os firms where #one firm in the first have a corresponding

Good day, For lack of a better solution (or perhaps I am ignorant to something more elegant), I have been bootstrapping panel data by hand so to speak and I would like to know if there is a way to define multiple variables in a loop using the loop variable. I found a post (here: https://stat.ethz.ch/pipermail/r-help/2002-October/026305.html ) that discussed naming multiple variables but it

Consider I have the following data: AgeRange AgeOfPerson PersonNo FriendsAtYear0 FriendsAtYear1 FriendsAtYear2 FriendsAtYear3 FriendsAtYear4 FriendsAtYear5 10 - 12 11 1 0 1 2 2 3 3 10 - 12 12 2 0 1 2 2 3 3 15 - 18 13 3 1 2 3 4 6 7 15 - 18 14 4 1 3 4 5 7 7 30 - 40 33 5 3 5 5 6 8 9 30 - 40 36 6 4 4 4 4 4 4 I want to plot the number of friends against number of years, as to show how friendships

Hi all, I'm somewhat of a novice in terms of programming, so I thought I'd come here to seek some help with an issue I'm having. I'm trying to model a glm using bigglm, but in spite of my best efforts, I cannot get it to work! Here is the particular line of code that is giving me trouble: >mod = bigglm(Pres/wt ~ Xdes, data=dat, family=poisson(), weights = ~wt, maxit=100,

Greetings, I just found out a bug in the function lmList of the package nlme with R 2.8.1 running under windows XP 32-bits. I have a data table with various columns corresponding to continuous variables as well as treatment variables taken on several years and several sites. Here is an example : Id year treatment A treatment B variable1 variable2 variable3 1

Dear All, I am working with a generalized linear mixed-effects model with poisson error using the lme4 package in R. I created a model with the lmer function including some main effects, three two way interactions and two random effects. The model works well, but I have troubles when removing on of the two-way interactions. The Warning message: "In mer_finalize(ans) : false convergence

To help in vhost analyzing, the following series adding basic tracepoints to vhost. Operations of both virtqueues and vhost works were traced in current implementation, net code were untouched. A top-like satistics displaying script were introduced to help the troubleshooting. TODO: - net specific tracepoints? --- Jason Wang (2): vhost: basic tracepoints tools: virtio: add a

To help in vhost analyzing, the following series adding basic tracepoints to vhost. Operations of both virtqueues and vhost works were traced in current implementation, net code were untouched. A top-like satistics displaying script were introduced to help the troubleshooting. TODO: - net specific tracepoints? --- Jason Wang (2): vhost: basic tracepoints tools: virtio: add a

My data: I have raw data points that form a logit style curve as if they were a time series. Which is to say they form 3 distinct lines with 3 distinct slopes in backwards z pattern. A certain class of my data looks essentially flat to the eye with marginal oscillation. What is important to me is the x value at which the state change is occurring, in other words, the break point Use of

Hi folks I am using the lmer function (in the lme4 library) to analyse some data where individuals are clustered into sets (using the SetID variable) with a single fixed effect (cc - 0 or 1). The lmer model and output is shown below. Whilst the fixed effects are consistent with stata (using xtmixed, see below), the std dev of the random effect for SetID is very very small (3.5803e-05)compared to

Recent debugging on vhost net zerocopy shows the need of tracepoints. So to help in vhost{net} debugging and performance analyzing, the following series adding basic tracepoints to vhost. Operations of both vhost and vhost_net were traced in current implementation. A top-like satistics displaying script were introduced to help the troubleshooting: vhost statistics vhost_virtio_update_used_idx

Recent debugging on vhost net zerocopy shows the need of tracepoints. So to help in vhost{net} debugging and performance analyzing, the following series adding basic tracepoints to vhost. Operations of both vhost and vhost_net were traced in current implementation. A top-like satistics displaying script were introduced to help the troubleshooting: vhost statistics vhost_virtio_update_used_idx

Dear R help, I'm working with regular 8-daily time-series from 2000 up till now and would like to be able to compare years with each other. E.g. by creating a monthplot via the result of the stl() method it looks ok> but I was wondering whether there exist other methods to plot the different years as lines on top of each other such that years can be compared with each other (temporal