similar to: R help, labeling the tick marks as I want

Folks, I have a strange situation, which I may have isolated as a bug report. Or, it could just be that there's something about R that I don't know. :-) I have attached the data file and the program file but don't know whether these attachments will make it into the list. Here is my bugreport.R program -- ---------------------------------------------------------------------------

I am attempting to manually specify x axis value labels (NOT x axis label as in xlab) on a density plot. Generally speaking, I would like to erase the default x axis point labels and replace them with arbitrary x axis point labels relating to specific CDF points. I am sure this can be done, but it isn't obvious to me how. Has anyone done this before? My R code follows if it helps (new

Dear all, I'm trying to remove some text after the period (a decimal point) in the data frame 'hi', below. This is one step in formatting a table. So I would like e.g. "2.0" to become "2" and "5.3" to be "5.3", where the variable digordered contains the number of digits after the decimal that I would like to display, in the same order in which

I don't understand this behavior. Why does the every data point get trashed by data.matrix when there is one non-numeric element in the array? Thanks. > temp GDP CPIYOY 19540 2098.1 garbage 19632 2085.4 0.9 19724 2052.5 0.8 19814 2042.4 1.1 > data.matrix(temp) GDP CPIYOY 19540 4 4 19632 3 2 19724 2 1 19814 1

Hi! I'm trying to do a lm() test on three objects. My problem is that R protests and says that the variable lengths differ for one of the objects (Sweden.GDP.gap). But I have double checked that the number of observations are the same. All three objects should contain 9 observations but R only accepts 9 observations in two of the objects. The third must have 10! Very confusing because there

Dear all, I have the following question. I have to fit the hierarchical model for the hypothesis concern the individual-level effects by controlling for the individual -level attributes and national-level contextual effects on individuals by using R. O have to obtain the estimates of the impact of the second-level (national: GDP per capita) effects on individuals ( in this instance the impact

Dear all, I was hoping someone could help with a ggplot question. I would like to generate a faceted bar chart, but missing data are causing problems. g<-structure(list(Date = structure(c(11322, 11687, 12052, 11322, 11687, 12052, 11322, 11687, 12052, 11322, 11687, 12052), class = "Date"), variable = c("Govt Revenues to GDP", "Govt Revenues to GDP",

hi, i need help on placing legend/text in a time series plot. here is what i am doing (i am using rw1022 on windoze 2000): #read data file gdpn <- scan("jngdpsa.dat", list(year=0, qtr=0, gdp=0)); gdpr <- scan("jrgdpsa.dat", list(year=0, qtr=0, gdp=0)); #convert to time series object gdpn <- ts(gdpn$gdp, frequency=4, start=c(1955,2)); gdpr <- ts(gdpr$gdp,

Hi there, I have a data.frame (pwt6) which I would like to transform: country year gdp MEX 1950 2 MEX 1951 5 BOL 1950 4 BOL 1951 12 ITA 1950 45 ITA 1951 2 This should be the result: year MEX.gdp BOL.gdp ITA.gdp 1950 2 4 45 1951 5 12 2 Right now I have this code (better - no code): country.label<-names(table(pwt6$country)) result<-data.frame(year=NULL) for(i in country.label) ?

Dear R users, I have two data frames that consist of statistical information for most countries around the world. One dataframe consists of the latitude and longitude ("coord.csv") of each country, while the other consists of 100's of different attributes ("countryattri.csv") for each country (like, GDP, Population, etc.). The data is organized with a header and then

Hello My data.frame (dat) contains many variables named var.names and others named var.names_var.id For example var.name <- c("gdp","inf","unp") var.id <- c("w","i") x <- paste(var.name, rep(var.id, each=length(var.name)), sep="_") How can I access variables in the dama.frame by names listed in x, for example to compute

List, I would like to set a variable to hold, say, the size of my plots in a Sweave document. i.e. something like the following in my '.Rnw' file: ============================================================================== smallPlotSize = 4 <<fig1, echo=false, results=hide, height=smallPlotSize, width=smallPlotSize, fig=true>>= dat <- read.table("

Hi all, I have a data set containing variables LOSS, GDP, HPI and UE. (I have attached it in case it is required). Having renamed the variables as l,g,h and u, I wish to run a Lasso Regression with l as the dependent variable and all the other 3 as the independent variables. data=read.table("data.txt", header=T) l=data$LOSS h=data$HPI u=data$UE g=data$GDP matrix=data.frame(l,g,h,u)

Hi, I am a new user to R. I am using strucchange to generate breakpoints: -------------------------------------------------------------------------------------- > res <- gbreakpoints(GDP.new ~ 1,data=a,h=2,breaks=5) > print(res) Optimal 6-segment partition for `lm' fit: Call: gbreakpoints(formula = GDP.new ~ 1, data = a, h = 2, breaks = 5) Breakpoints at observation number:

Hi, I am new to R. I am using strucchange to get the breakpoints in time series dataset. So the problem I am facing is: I want to link the result generated by the breakpoints to further analysis (for eg. generating volatility for each group). The result is in following form: --------------------------------------- > res <- gbreakpoints(GDP.new ~ 1,data=a,h=2,breaks=6) > res

I get the following error message after using the sysfit package's function 'systemfitClassic': Error in data[[eqnVar]] : subscript out of bounds When I do this: MSYS1 <- cbind(Y, Num, F, PO, PD, GO, GD) MigOLS1 <- systemfitClassic("OLS", F ~ PO + PD + GO + GD, eqnVar = "Num", timeVar = "Y", data = MSYS1) and I get this error message: Error in

I'm writing a paper aimed at motivating the use of GEE within the field of economics. However, after computing using the geeglm function, I noticed there's one intercept in the summary output. I assume this means the function is pooling the data. That means my code is not what I want. I want a "fixed effects" model, meaning I want the intercept to vary by cluster. Here's

Dear R users I have a data set which has five variables. One depenedent variable y, and 4 Independent variables (education-level, householdincome, countrygdp and countrygdpsquare). The first two are data corresponding to the individual and the next two coorespond to the country to which the individual belongs to. My data set does not make this distinction between individual level and country

Hello again! thanks to all who helped with overlay plots - v. easy in the end. Anyway, another new(ba)bee type question - the gurus will cringe I'm sure! Q. simple R function mm <- function (u) { x <- u$GDP x m <- mean(x) m } When the function is called the vector "x" does not get printed from within the function, but the mean value "m" does, why? I

Hi, I am trying to run a panel regression where I have a matrix of observations and a matrix of independant variables - examples would trying to predict countries's GDP with their data on education, FDI, tax rates, over time. For the purpose of simplicity, my data would be: dep = matrix(rnorm(50),ncol=5) indep1 = matrix(rnorm(50),ncol=5) indep2 = matrix(rnorm(50),ncol=5) >From what I