similar to: ksmooth in SPLUS vs R

Hi There I have a lm object with 4 parameters and I want to test wether 2 parameters are equal using a Wald test (basically b1=b2 or b1-b2 =0). In the help file from R it says that under ANOVA the optional arguments " Terms" or "L" test whether a linear combination is equal to 0. I tried; >anova(m1, Terms = Beta1-Beta2=0) but I get the error: Object " Beta1"

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'd like to superimpose a ksmooth() onto a barplot(). My data is: > d 2009-06-20 2009-06-21 2009-06-22 2009-06-23 2009-06-24 2009-06-25 2009-06-26 2009-06-27 2009-06-28 2009-06-29 2009-06-30 2009-07-01 2009-07-02 Same Breed (B) 12.64 21.08 13.52 12.51 13.71 9.91 14.24 7.18 11.81 5.92 12.04 17.96

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]]

Hi all! I'm new to this forum so please excuse me if I don't conform perfectly to the protocols on this board! I'm trying to get an estimate of true prevalence based upon results from an imperfect test. I have various estimates of se/sp which could inform my priors (at least upper and lower limits even if with a uniform distribution) and found the following code on this website..

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]]

Dear all, Does anybody know how to get more evaluation points in performing Nonparametric analysis of repeated measurements data with "sm" library. The following command gives the estimation for 50 points, by I would like to increase to 100 points But I do not know how to do that. library(sm) provide.data(citrate, options=list(describe=FALSE)) provide.data(dogs,

I'm using nonparametric regression (packeges ksmooth and ks). My question: is there any way to compute confidence bands (or variability bands) with R. Confidence bands for functions are intervals [CLO(x);CUP(x)] such that with probability 1-alpha the true curve is covered by the band [CLO(x);CUP(x)]. Thanks very much for any help you can offer. Michael G??lger

I was trying to plot some data in R. I used the following code to draw a loess fit and got the output as >?lines(lowess(log(abs(t(res))), log(abs(t(synthesised)))), col="red") Error in lowess(log(abs(t(res))), log(abs(t(synthesised)))) :?? NA/NaN/Inf in foreign function call (arg 1) Then I thought to use your Limma package for background correction. Do you think it's a right

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 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 am doing kernel density plots, and am trying to make the lines thicker. I comparing three groups, in sm.density.compare. I tried changing lwd to make the line sthicker right on the density compare call, but was not able to do it. There is not an option in sm.options to specify line thickness, as well as cex.ylab or cex.xlab- I tried it and it does not change the thickness of the lines.

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

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]]