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Dear R help, I have some readings in three dimensions (x, y, z) and an amplitude for each. I'd like to visualize the data using ggplot, using tile plots, as I have some additional point data I would like to eventually overlay on the tile plots. I would like to subset the data by sections, slices if you will, in the z dimension, and plot the data for that slice. I can do all of this, but am

Dear all, I?m having some problems getting optim with method="Nelder-Mead" to work properly. It seems like there is no way of controlling the step size, and the step size seems to depend on the *difference* between the initial values, which makes no sense. Example: f=function(xy, mu1, mu2) { print(xy) dnorm(xy[1]-mu1)*dnorm(xy[2]-mu2) } f1=function(xy) -f(xy, 0,

Full_Name: Somkiat Apipattanavis Version: 2.1.1 OS: Windows Submission from: (NULL) (128.138.44.123) Bug found in predict.locfit for density estimation # Example of bug found in prdict.locfit (Locfit) library('locfit') # generate data y =c(4281,2497,4346,5588,5593,3474,4291,2542,5195,4056, 3114,2864,4904,7625,3377,4001,4999,7191,8062,5668) x1=c( 0.258729, 1.460156, 0.192323,

Apologies for the coming to this late... 1. By now I hope Somkiat has realized that R-bugs is not the place to report problems in contributed packages. Please direct such reports to the package maintainer. 2. This is really user error. predict() expect the newdata to be a data frame containing variables with the same names as those used in the fitting process. E.g., you fitted the model with

Hi, I'm a newbie to R. My knowledge of statistics is mostly self-taught. My problem is how to measure the effect of users in groups. I can calculate a particular attribute for a user in a group. But my hypothesis is that the user's attribute is not independent of each other and that the user's attribute depends on the group ie that user's behaviour change based on the group. Let