similar to: question about 3-d plot

Hi All, I am using R 2.11.0 on a Ubuntu machine. I have a time series data set and want to run rolling regressions with it. Any suggestions would be useful. Here are the details: (1) I convert relevant variables into time series objects and compute first differences: vad <- ts(data$ALLGVA/data$GDPDEF, start=1948, frequency=1) emp <- ts(data$ALLEMP, start=1948, frequency=1) vad.dif1 <-

Hi All, I am using R 2.11.0 on a Ubuntu machine. I estimated a model using "tsls" from the package "sem". Is there a way to get Newey West standard errors for the parameter estimates? When estimating the model by OLS, I used "NeweyWest" from the package "sandwich" to get HAC standard errors. But, I am not able to use the same method with the results of the

Hi R Users, I have a dataframe like this: id x rho A 1 0.1 B 20 0.5 C 2 0.9 ... I want to do a scatter plot of "x" versus "rho" but for each point on the scatter plot I want the corresponding entry for "id" instead of points. In STATA I can do so by twoway (scatter x rho, mlabel(id)) How can I do the same in R? I am sure there is some simple way to do

Hi All, I have a data frame with a group of variables named b1, b2, b3, ..., b18. These variables take the value 1, 2 or NA. For each observation, I want to do some computation by looping over the values for the group of variables: b1 to b18. In STATA I would do: forval i=1/18 { --- use b`i' for computation ---- } How can this be done in R? Deepankar

Hi! I am using R version 2.7.0 and am working on a panel dataset read into R as a dataframe; I call it "ex". The variables in "ex" are: id year x id: a character string which identifies the unit year: identifies the time period x: the variable of interest (which might contain NAs). Here is an example: > id <- rep(c("A","B","C"),2) >

Hi! As per Thomas' advice, I upgraded R by using "update.packages()" and got the following warning messages: Warning messages: 1: installation of package 'lmtest' had non-zero exit status in: install.packages(update[, "Package"], instlib, contriburl = contriburl, 2: installation of package 'quadprog' had non-zero exit status in: install.packages(update[,

I am trying to maximise a complicated loglikelihood function with the "optim" command. Is there some way to get to know the estiamtes at each iteration? When I put "control=list(trace=TRUE)" as an option in "optim", I just got the initial and final values of the loglikelihood, number of iterations and whether the routine has converged or not. I need to know the

Hi All, I am trying to do an ML estimation in R. My likelihood function has several nested loops and so it takes a lot of time (days when I use the genetic algorithm for optimization) for the optimization to finish. Unable to avoid loops, I am thinking of writing the likelihood function in C++ and calling it from within R when using *optim()*. I found that one can call C functions (once they have

Hi All, I have a very simple question about a time series object: how to access values for a particular year and quarter (say)? Suppose, following http://www.stat.pitt.edu/stoffer/tsa2/R_time_series_quick_fix.htm I have read in data as a time series; here is how it looks. * Qtr1 Qtr2 Qtr3 Qtr4 1960 0.71 0.63 0.85 0.44 1961 0.61 0.69 0.92 0.55 . . . . .

I tried to install the package "tseries" but could not do so. Any suggestions are welcome. I am using Ubuntu Linux and here is what I did: $ sudo R Then once in R, I did > install.packages("tseries", dep=TRUE) which gave a long list of errors. Going through them, I saw that the basic problem was that the package "grid" was not found by the packages (like

As part of carrying out a complicated maximum likelihood estimation, I am trying to learn to program likelihoods in R. I started with a simple probit model but am unable to get the code to work. Any help or suggestions are most welcome. I give my code below: ************************************ mlogl <- function(mu, y, X) { n <- nrow(X) zeta <- X%*%mu llik <- 0 for (i in 1:n) { if

Hello, I am drawing contour lines for a function of 2 variables at one level of the value of the function and want to include a small arrow in any direction of increase of the function. Is there some way to do that? Below is an example that creates the contour lines. How do I add one small arrow on each line in the direction of increase of the function (at some central point of the contour

Hi all, I have been previously been using scatterplot3d package to create some graphs but unfortunately it does not allow me to rotate the plot on all three axis. The cloud() function in the lattice package does allow me to do so. When I was using scatterplot3d I was using a script (Shown Below) to calculate the mean, quartiles and range limits for all three axis and I was representing that on the

Hi, I have two further comments/questions about large datasets in R. 1. Does R's ability to handle large datasets depend on the operating system's use of virtual memory? In theory, at least, VM should make the difference between installed RAM and virtual memory on a hard drive primarily a determinant of how fast R will calculate rather than whether or not it can do the calculations.

Hi R users! I am new to R. When I try to attach a simple dataset using the attach() command, I get the following message: > attach(data1) The following object(s) are masked from package:base : write Can someone tell me what this means? (`write' is the name of a variable in the dataset). And, do I need to do do something about this. Thanks.

Hi All, I have data on the sequence of births for families with completed fertility cycle (in a data frame); the relevant variables are called b1, b2, b3, b4, b5, b6 and record the birth of the first, second, ..., sixth child. So, b1=1 if the first birth is male, b1=2 if the first birth is female, and b1=NA if the family did not record any first birth. Similarly for b2, b3, b4, b5 and b6. I

Hi R users, I have a couple of questions about some problems that I am facing with regard to numerical integration and optimization of likelihood functions. Let me provide a little background information: I am trying to do maximum likelihood estimation of an econometric model that I have developed recently. I estimate the parameters of the model using the monthly US unemployment rate series

R Users: I am trying to estimate a model of fertility behaviour using birth history data with maximum likelihood. My code works but is extremely slow (because of several for loops and my programming inefficiencies); when I use the genetic algorithm to optimize the likelihood function, it takes several days to complete (on a machine with Intel Core 2 processor [2.66GHz] and 2.99 GB RAM). Computing

Hi everyone - This came up within the last day -- Jim's response to Deepankar is pasted below. There are probably lots of reasons, but what is the advantage to using .temp over, say, temp? I often find myself writing temporary objects -- should I use the . preface? What would be the advantages to doing so? Thanks in advance for what will surely be a collection of illuminating responses.

I'm using the 'cloud' function in the 'lattice' package to produce multi-panel 3D scatter plots. The range of the values used vary much between each panel (especially on the z axis), so I wish the axis limits to be calculated based on the (conditional) data. Here's a minimal example: library(lattice) z=1:200 x=runif(200) y=runif(200) s=factor(rep(c(1,2),each=100))