similar to: Superimpose ksmooth() onto barplot

Dear R Users, Before running ksmooth( ), a suitable bandwidth selection is needed. I use some functions for this task and receive these results for my data: width.SJ(y,nb=100,method="ste") : 40.25 bcv(y,nb=100) : 40.53 ucv(y) : 41.26 bandwidth.nrd(y) : 45.43 After implementing the function ksmooth(x,y, bandwidth= each of abovementioned bandwidths), I have some NAs

Apologies in advance if my comments don't help, in which case, no need to respond, but I noted in ?ksmooth: "bandwidth the bandwidth. The kernels are scaled so that their quartiles (viewed as probability densities) are at ? 0.25*bandwidth." So, could this be a source of the discrepancies you cited? Given that ?ksmooth explicitly says: "Note: This function was implemented for

Dear Sir, Madam, or to whom this may concern, my name is Jan Failenschmid and I am a Ph.D. student at Tilburg University. For my project I have been looking into different types of kernel regression estimators and corresponding R functions. While comparing different functions I noticed that stats::ksmooth returned different estimates for the same bandwidth as other kernel regression estimators

I am working with a model that I have to estimate a nonparametric function. The model is partial linear i.e. Y=X$\beta$ + f(z) + $\epsilon$ I am using the ' double residual methods' Robinson (1988) Speckman (1988) where I estimate a nonparametric function for each of the parametric variables in terms of the nonparametric one i.e. X[,i]=g(Z)+ u this is done because I need the $E(

Hi Every Body, I don't know why some regression functions have no related prediction function. For example lowess, loess, lokerns, lpridge, lpepa, and ksmooth. What could help? Is there any global or wrapper function so that can help? Regards, Amir Safari --------------------------------- [[alternative HTML version deleted]]

Dear R user, My input data, positive and negative, is complete without missing data. After running ksmooth( ) , I receive for $y , many NAs. What could be the reasons and how can I receive complete output? So many thanks for any help. Amir Safari --------------------------------- [[alternative HTML version deleted]]

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 <-

Hi, Consider the Nottingham temperature and the Sunspot data: >data(nottem) >data(sunspot) Assume that we may model each data set by a nonparametic autoregressice model of the form Yt = m(Yt-1) +et, What are the value of x and y for using function ksmooth(x,y,"normal",bandwidth=0.01)? Thanks a lot! Owen

Hello, I'm trying to superimpose a line plot onto a histogram but I'm not having any luck. I've attached the dataset. What I did was: > hist(data,freq=F) Now I'm trying to superimpose the following points with a line connecting them onto the histogram: x y 100 0.535665393824959 200 0.212744329736556 300 0.0844933242968584 400 0.0335572838043417 500

Hello, I want to do regression or missing value imputation by knn. I searched r-help mailing list. This question was asked in 2005. ksmooth and loess were recommended. But my case is different. I have many predictors (p>20) and I really want try knn with a given k. ksmooth and loess use band width to define neighborhood size. This contrasts to knn's variable band width via fixing a

Hi Does R have a function or has someone written a function to draw a 3d surface from a scatter plot of values using either ksmooth or locpoly. OR a transform function a that merges x relation z and y relation z to (x,y) relation z? I tried out scatterplot3d but it seems it would take a bit of work to get scatterplot3d to draw a curved surface. Lawrence

Hi, I just started with R and I found that there are many options to rearrange the data to do mixed models. I want to use the reshape function. I have 2 between subject variables and one within. I was able to change the data structure but still - the result of the aov functions are calculating everything as a within subject. the table looks like this: SerialNo breed treatment distance_1

Is it possible to access the described class in a shared behavior? I''m trying to do something like this: describe "Siberian feline", :shared => true do described_class_instance_as :feline, :name => "fluffy", :breed => "Siberian" # or maybe before(:all) do @feline = described_class.new(:name => "fluffy", :breed =>

Hi again List: This time I have the following: > setClass("dog",representation(breed="numeric")) [1] "dog" > woof <- function(x=1:10) { + if(!is.numeric(x))stop("Must have numeric data") + y <- new("dog",breed=x) + return(y) + } > setMethod("plot","dog", + function(x,y,...) { +

Hi has anyone succeeded in installing R on DEC alpha OSF 4.0 with gcc/g77 ? The PLATFORMS file mentions successful installtion on OSF 3.2 using cc. Here is the output I get when trying to compile: ld -shared -o eda.so line.o smooth.o ld: Warning: Unresolved: floor ceil rsort __exc_add_pc_range_table __exc_add_gp_range __exc_remove_pc_range_table __exc_remove_gp_range make[4]: Leaving

OK, I know I''m doing something bone-headed, but I can''t for the life of me figure it out. I''ve read the test fixtures Rdoc about eight dozen times, and it says (to me) that if I have a YAML fixture file, dogs.yml that looks like this: fido: id: 1 breed: Terrier fifi: id: 2 breed: Poodle Then I can include fixtures :dogs in my functional test, and

Hello, I am trying to get fitted/estimated values using kernel regression and a triangular kernel. I have found packages that easily fit values from a kernel regression (e.g. ksmooth) but do not have a triangular distribution option, and density estimators that have triangular distribution options that I can't seem to use to produce estimated values (e.g. density). Any help is appreciated.

Good evening,I am Marta Colombo, student of "Politecnico di Milano". I'm studying Local Regression Techniques such as loess, smoothing splines and kernel smoothers. Choosing "symmetric" for the argument "family" in loess function it is possible to produce a robust estimate , in function smooth.spline and ksmooth I didn't find this possibility. Well, is there a

Hi all, I am looking for a command for doing 2D filtering (rectangular or Gaussian) in R... I have looked at ksmooth, filter and convolve but they seem to be 1D... Any thoughts? Thanks a lot! [[alternative HTML version deleted]]

Hi all I hope you might help me with some aspects of producing a graph in lattice. There are three things I have struggling with and that is: 1. to separate the horizontal box rows from each other; 2. to change the colour of the horizontal and vertical strips to white; and 3. to place the axes labels on the left y axes and on the bottom x axes. I would really appreciate some help. I have put the