similar to: smoothing with the Gaussian kernel

Hello all, I would like to use the Nadaraya-Watson estimator assuming a Gaussian kernel: So far I sued the library(sm) library(sm) x<-runif(5000) y<-rnorm(5000) plot(x,y,col='black') h1<-h.select(x,y,method='aicc') lines(ksmooth(x,y,bandwidth=h1)) which works fine. What if my data were clustered requiring a bandwidth that varies with x? How can I do that? Thanks in

All: I am trying to use gam in a scatterplot smoothing problem. The data being smoothed have greater 1000 observation and have multiple "humps". I can smooth the data fine using a function something like: out <- ksmooth(x,y,"normal",bandwidth=0.25) plot(x,out$y,type="l") The problem is when I try to fit the same data using gam out <-

Dear list members, I am trying to understand this output from the smoothing package locfit (1.5-4, running on R 2.8.1 on Windows Vista 64 bit). # sample code x<-1:100 y<-rnorm(100) fit<-locfit(y~x,family="gaussian") #default parameters are fine plot(fit,band="global") #plot seems "reasonable", confidence bands use a global estimate of variance

Hello, I'm new to R, and I would like to know if there is a way to smooth a curve using a Gaussian smoothing with R. Thank you very much, TDB -- View this message in context: http://www.nabble.com/Gaussian-Smoothing-tp14321313p14321313.html Sent from the R help mailing list archive at Nabble.com.

useR's, I want to randomly generate 500 numbers from the standard normal distribution, i.e. N(0,1), but I only want them to be generated in the range -1.5 to 1.5. Does anyone have a simple way to do this? Thanks, dxc13 -- View this message in context: http://www.nabble.com/simple-random-number-generation-tp18642611p18642611.html Sent from the R help mailing list archive at Nabble.com.

>From what I understand, loess in R uses the standard tri-cube function. SAS/INSIGHT offers loess with Gaussian weights. Is there a function in R that does the same? Also, can anyone offer any references comparing properties between tri-cube and Gaussian weights in LOESS? Thanks. - Andr? -- View this message in context:

useR's, I am trying trying to find out if there is a faster way to do a certain computation. I have successfully used FOR loops and the apply function to do this, but it can take some time to fully compute, but I was wondering if anyone may know of a different function or way to do this: > x [1] 1 2 3 4 5 > xk [1] 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 I want to do:

useRs, I am looking to find the minimum positive value of some data I have. Currently, I am able to find the minimum of data after I apply some other functions to it: > x [1] 1 0 1 2 3 3 4 5 5 5 6 7 8 8 9 9 10 10 > sort(x) [1] 0 1 1 2 3 3 4 5 5 5 6 7 8 8 9 9 10 10 > diff(sort(x)) [1] 1 0 1 1 0 1 1 0 0 1 1 1 0 1 0 1 0 > min(diff(sort(x))) [1] 0

useR's, I have a matrix given by the code: mat <- matrix(c(rep(NA,10),1,2,3,4,5,6,7,8,9,10,10,9,8,NA,6,5,4,NA,2,1,rep(NA,10),1,2,3,4,NA,6,7,8,9,10),10,5) This is a 10x5 matrix containing missing values. All columns except the second contain missing values. I want to delete all columns that contain ALL missing values, and in this case, it would be the first and fourth columns. Any column

Hi all, I cannot think of the technical name of this plot, but I want to create a plot with the data below that looks like two back-to-back horizontal bar plots. Ideally, there would be a vertical line in the center of the plot at zero, and on the right hand side would be 4 bars representing the values for 2007, and on the left side of the vertical line would be the corresponding values for 2005.

useR's I am trying to color the points on a scatter plot (code below) with two colors. Red for values 0.5 -1.0 and blue for 0.0 - .49. Does anyone know a easy way to do this? x <- runif(100, 0, 1) y <- runif(100, 0, 1) plot(y ~ x, pch=16) Thanks, dxc13 -- View this message in context: http://www.nabble.com/color-ranges-on-a-2D-plot-tp14893457p14893457.html Sent from the R help

useR's, I have several matrices of size 4x4 that I want to calculate means of their respective positions with. For example, consider I have 3 matrices given by the code: mat1 <- matrix(sample(1:20,16,replace=T),4,4) mat2 <- matrix(sample(-5:15,16,replace=T),4,4) mat3 <- matrix(sample(5:25,16,replace=T),4,4) The result I want is one matrix of size 4x4 in which position [1,1] is the

Hi useR's I have created a simple map of the world using the following code: m <- map(xlim=c(-180,180), ylim=c(-90,90)) map.axes() I then create a grid of dimension 36x72 using the code: map.grid(m, nx=72, ny=36, labels=FALSE, col="black") This gives 2592 grid cells. In a separate data set of dimension 36x72, I have 2592 temperature values (some missing values are present)

Hi all, I have a data frame that looks like such: LATITUDE LONGITUDE TEMPERATURE TIME 36.73 -176.43 58.32 1 50.95 90.00 74.39 1 -30.42 5.45 23.26 1 15.81 -109.31 52.44 1 -80.75 -144.95 66.19 2 90.00 100.55 37.50 2

useR's I am trying to compare two vectors that have the same length. More specifically, I am interested in comparing the corresponding positions of each element in the vector. Consider these two vectors of length 20: v1 <- 2 2 4 NA NA NA 10 NA NA NA NA NA NA NA NA NA NA NA NA NA v2 <- NA 4 NA NA NA NA 10 NA NA NA NA NA NA NA NA NA NA NA

Dear List, I am trying to draw a rectangular plane using the persp function, however I can't seem to get it to work. I want the length along x1 axis to be between 1 and 3 and the length along the x2 axis to be between 1 and 4. All z values for x1 should be equal (say, z=1) because this is a plane, not a cube. Below is my current code. Any help is appreciated Thanks in advance dxc13 x

useR's, I want to match the real number elements of a list that has 3 matrices as its elements and then average those numbers. I think I am close, but I can't get it to quite work out. For example, > a <- list(matrix(c(10,NA,NA,12,11, > 10,13,NA,14,12),ncol=2),matrix(c(10,12,15,13,11, > 13,NA,NA,12,10),ncol=2),matrix(c(10,15,NA,13,NA, 13,12,NA,NA,10),ncol=2)) > a [[1]]

Hi all, I have posted similar questions regarding this topic, but I just can't seem to get over the hump and find a straightforward way to do this. I have attached my file as a reference. Basically, the attached file is a 5 degree by 5 degree grid of the the world (2592 cells), most of them are NA's. I just want to be able to plot this grid over a world map and color code the cells. For

useR's, I want to apply this function to the columns of a data frame: u[u >= range(v)[1] & u <= range(v)[2]] where u is the n column data frame under consideration and v is a data frame of values with the same number of columns as u. For example, v1 <- c(1,2,3) v2 <- c(3,4,5) v3 <- c(2,3,4) v <- as.data.frame(cbind(v1,v2,v3)) uk1 <- seq(min(v1) - .5, max(v1) + .5,

useR's, I get these 2 errors when I run "R CMD check" on my package, and I cannot figure out how to get around them. Does anyone have any ideas? If it is of any help, I use Windows XP. ... * checking replacement functions .... OK * checking foreign function calls ... OK * checking R code for possible problems ... NOTE Error in inDL(x, as.logical(local), as.logical(now), ...):