similar to: Gaussian Smoothing

useR's, Does anyone know what function or package allows one to specify use of the Gaussian kernel to smooth a data set, or is this just the default for most functions? Thanks, dxc13 -- View this message in context: http://www.nabble.com/smoothing-with-the-Gaussian-kernel-tp19323294p19323294.html Sent from the R help mailing list archive at Nabble.com.

Hi Paul, Take a look at gam() from package mgcv (gam = generalized additive models), maybe this will help you. GAMs can work with other distributions as well. Generalized additive models consist of a random component, an additive component, and a link function relating these two components. The response Y, the random component, is assumed to have a density in the exponential family. I am not sure

Hi, I hope somebody can help me with this issue: I am doing population pyramids using the barplot command, so in the left side I have male age structure and in the right side the female age structure. To plot the male age structure I put the data in negative numbers. Now, I want to change the sign in the bar plot in such way that I have no-sign numbers, both in left and right side of the graph. I

I have a matrix containing means and CIs (lower and upper in two columns, so three columns for every data point) for several points. I have to build a graph of these means accompained by the CIs (as wiskers). No problems with making the graph of means, but I don't know how to introduce CIs. Can anybody advise? -- View this message in context:

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 trying to do cor(x1,x2) and I get the following error: Error in cor.default(x1, x2) : missing observations in cov/cor A few things: 1. I've used cor() many times and have never encountered this error. 2. length(x1) = length(x2) 3. is.numeric(x1) = is.numeric(x2) = TRUE 4. which(is.na(x1)) = which(is.na(x2)) = integer(0) {the same goes for is.nan()} 5. I also try

The myoglobin sequence, with reference number NM_005368 in Gen bank, has the following frequencies of DNA nucleotides: A C G T 237 278 309 242 Do these data provide sufficient evidence, at the 1% level of significance, that the DNA nucleotides have an unequal distribution, that is the DNA nucleotides are not evenly utilised? Clearly state your hypothesis, test statistic and conclusion.

Hi, the standard errors of the coefficients in two regressions that I computed by hand and using lm() differ by about 1%. Can somebody help me to identify the source of this difference? The coefficient estimates are the same, but the standard errors differ. ####Simulate data happiness=0 income=0 gender=(rep(c(0,1,1,0),25)) for(i in 1:100){ happiness[i]=1000+i+rnorm(1,0,40)

I'm beginner in R! I have a lot of problems on R..... I have three questions about GAM 1. What is the function of Gaussian distribution in GAM?(if I choose family is Gaussian) Is it used in the predictand value (Y)? 2. How to plot a graph the gam function? For example: y<-gam(a~s(b),family=gaussian (link=log) ,Data) how to plot x axis is s(b) and y axis is log a??? 3. if I use GAM to

Hi So my particular problem is this: I have a row vector of length 5200 elements - specifically created by x<-rbinom(5200,1,0.5) y<-matrix(x,nrow=1,ncol=5200) y now, each element is either a 0 or a 1 - e.g. it could be (0,1,1,1,1,0,0,0,1,1,1) e.t.c. when the element is a 1, i need to multiply a number (say 1000) by 1.005, and if it is 1 again, multiply it _again_ by 1.005. so for

I am writing a rd doc, and need to use "#" in a url adress. This would make: \url{http://www.xxxx.org/myfolder/#myanchor} Of course, I suppose this will not work because # is a special character starting a comment line in the rd dialect. I did not found a similar example in "Writing R exentions". I am not sure bout using \dQuote{a quotation}), and use \sQuote and \dQuote

Hi, As far as I know, there exist some programs via the function INLA, but I'm so curious if there is a specific function directly used to fit the log Gaussian Cox process model and predict the latent Gaussian field. That is, if I have a data points, then I input it in the function and don't need to revise the program. Thanks for your help. Joseph -- View this message in context:

I have time-series data on approval ratings of British Prime Ministers. The prime ministers dating from MacMillan onward till today are coded as dummy variables and the approval ratings are entered for each month. I want to know the mean value of the approval rating of each Prime Minister in the dataset and the approval rating during his/her first month and last month as PM. What R code should

Hi I'm trying to do a GAM analysis and have the following codes entered into R (density is = sample number, alive are the successes) density<-as.real(density) y<-cbind(alive,density-alive) library(mgcv) m1<-gam(y~s(density),binomial) at which point I get the following error message Error in smooth.construct.tp.smooth.spec(object, dk$data, dk$knots) : A term has fewer unique

loess() should be able to do robust 2D smoothing. There's no natural ordering in 2D, so defining running medians can be tricky. I seem to recall Prof. Koenker talked about some robust 2D smoothing method at useR! 2004, but can't remember if it's available in some packages. Andy From: Vladislav Petyuk > > Hi, > Are there any multidimenstional versions of runmed() and >

Dear R users, I have a question about the plot with the package gam. I need to plot different main effect functions, related to different gam models, in the same graphics (i.e. the same covariate about different models). I used the plot.gam e preplot.gam documentations. Using preplot.gam I can plot the single function but I'm not able to put all the functions together. Does anybody can help

Hi, I have seen a discussion in the R-help asking whether nonparametric manova has been implemented in R yet. This discussion is form March 2006 and there seemed to be no package or function implemented at the time. Has this changed? Is there a package that provides nonparametric manova as in McArdle and Anderson (2001) and Anderson (2001) now? Thanks, Daniel ------------------------- cuncta

Hi, I am trying to extract some numbers from a text string. The problem is that the delimiting symbols are identical so that I do not know how to tell "sub" between which of them to extract. The string looks like this 12/01/03/08 The extracted variables should look like: x1=12 x2=01 x3=03 x4=08 If anybody could help or point me to useful help, I would be greatful. Cheers, Daniel

I am trying to get the function "Models" to work each time there is an instance of k. This code will stop after the first model is complete. I need it to come back and pass the next value of c into the "Initial.State" function. any ideas? col<-c(23:28) #Setup for(k in col){ Initial.State(Response=zample[,c(k,29)], Explanatory=zample[,variable_columns],

I have a data set like the following: subject visit x1 1 1 0.5 1 2 1.2 1 3 0.7 2 1 0.4 2 2 0.6 2 3 1.0 ..... where x1 is the interval between the two visits. Now I want to calculate the cumulative intervals since the beinging, for example subject visit x1 cum 1 1 0.5 0.5 1 2 1.2 0.5+1.2 1 3 0.7 0.5+1.2+0.7 2 1 0.4 0.4 2 2 0.6 0.4+0.6 2 3 1.0 0.4+0.6+1.0 ..... is there an easy to generate the