similar to: scatter plot question

Hi R Users, I have produced a simulated scatter plot of y versus x tightly clustered around the 45 degree line through the origin with the following code: x <- seq(1,100) y <- x+rnorm(100,0,10) plot(x,y,col="blue") abline(0,1) Is there some way to generate a 3-dimensional analogue of this? Can I get a similar simulated scatter plot of points in 3 dimensions where the points

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 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 . . . . .

Hi... In Stata, there is the ability to display scatter plots with data points at the same (x,y) location, using the 'jitter' command of the twoway scatter stata command. Anyone know of a way that I can do the equivalent thing in R? For non-Stata readers, if jitter is enabled in stata, and n-points would be at the same (x,y) location, the points are offset a bit (according to

Dear List, I have a wrapper function that draws a graph that I'd like to use in a vector-like manner. The for-loop version I currently use is below. library(ggplot2) data(economics) h <- 600 w <- 800 #---------------------------------------------------------- draw_metric_by_date <- function( df, i, smooth=FALSE, BASEPATH ) { mlabel <- names(df)[i] qmetric

I've tried without success to calculate interaction and main effects contrasts using R. I've found the functions C(), contrasts(), se.contrasts() and fit.contrasts() in package gmodels. Given the url for a small dataset and the two-way anova model below, I'd like to reproduce the results from appended SAS code. Thanks. --Dale. ## the dataset (from Montgomery) twoway <-

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've been running loglinear models for three-way tables: one of the variables having three levels, and the other two having two levels each. An example looks like below: > yes.no <- c("Yes","No") > switch <- c("On","Off") > att <- c("BB","AA","CC") > L <- gl(2,1,12,yes.no) > T <-

Hi, all There are 62 samples in my data and I tested 3 times for each one, then I want to use ICC(intraclass correlation) from irr package to test the consistency among the tests. *combatexpdata_p[1:62] is the first text results and combatexpdata_p[63:124] * is the second one and *combatexpdata_p[125:186]* is the third. Here is the result:

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

> install.packages("rggobi", repos="http://ggobi.org/r/") Warning in install.packages("rggobi", repos = "http://ggobi.org/r/") : argument 'lib' is missing: using /Users/hadley/Library/R/library/ Reading symbols for shared libraries . done Program received signal EXC_BAD_ACCESS, Could not access memory. Reason: KERN_INVALID_ADDRESS at

Hi r-users,   I would like to solve for z values using newton iteration method.  I 'm not sure which part of the code is wrong since I'm not very good at programming but would like to learn.  There seem to be some output but what I expected is a vector of z values.  Thank you so much for any help given.   newton.inputsingle <- function(pars,n) {  runi    <- runif(974, min=0, max=1)

I've only been using R on and off for 9 months and started using the glasso package for sparse covariance estimation. I know the concept is to shrink some of the elements of the covariance matrix to zero. However, say I have a dataset that I know has some underlying "baseline" covariance/correlation (say, a value of 0.3), how can I change or incorporate that into to the

Hello, I get a segfault when running glmmboot in my own package glmmML. Has happened many time before, but this time I get no hint of where in my C functions the error might be. I give the output below. Can this be an R bug? I suspect it has to do with repeated calls to 'vmmin' like this: for (...){ vmax = vmaxget(); vmmin(*p, b, &Fmin, bfun,

We are having problems building R on Red Hat Linux 6.0/Sparc. R compiles with no problem but then it fails "make tests". Specifically, the line eigen(cbind(-1,c(1:2,0),0:2)) # complex values causes a segmentation fault. Previous versions of Red Hat Linux did not give this problem. The eigen() function is one of the rare cases in the base library where Fortran code is called via the

I'm trying to implement a recursive function using integrate, and I suspect I need a Vectorize somewhere, but I can't suss it out. Any help would be appreciated. I've tried traceback() and various debugging ideas to no avail (most likely due to my inexperience with these tools.) Here's what I have. Nk <- function(m, C) { if (length(m) > 1) { rho <- C[1, -1]

Dear all, I need to do some calculation where the code used are below. I get error message when I choose k to be large, say greater than 25. The error message is "Error in integrate(temp, lower = 0, upper = 1, k, x, rho, m) : the integral is probably divergent". Can anyone give some help on resolving this. Thanks. Hannah m <- 100 alpha <- 0.05 rho <- 0.1 F0

Hi R-users,   I have this code here: library(numDeriv)   fprime <- function(z) { alp  <- 2.0165;   rho  <- 0.868;   # simplified expressions   a      <- alp-0.5   c1     <- sqrt(pi)/(gamma(alp)*(1-rho)^alp)   c2     <- sqrt(rho)/(1-rho)   t1     <- exp(-z/(1-rho))   t2     <- (z/(2*c2))^a   bes1   <- besselI(z*c2,a)   t1bes1 <- t1*bes1   c1*t1bes1*t2 }   ## Newton

I wanted to try out package distrMod, so I did > install.packages('distrMod') > library(distrMod) and played around, saved and quit. Now whenever I start up in this directory, I get distr and lots of other stuff loaded and lots of messages. How do I keep it from automatically loading, other than starting over in another directory? I read ?Startup, but I couldn't suss out

Suppose F(x, y; rho) is the cdf of a bivariate normal distribution, with standardized marginals and correlation parameter rho. For any fixed x and y, I wonder if F(x, y; rho) is a monotone increasing function of rho, i.e., there is a 1 to 1 map from rho to F(x, y; rho). I explored it using the function pmvnorm in package mvtnorm with different x and y. The plot suggests the statement may be true.