similar to: FW: Kernel smoothing with bandwidth which varies with x

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

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

Hello everyone, Thank you for this. Nonetheless it is not exactly want i need. I need mydata[[1]] to provide the values for all 3 variables (Y, X1 and X2) of the first imputation only. As it stands it returns the whole database. Any ideas? Best, ioanna ________________________________ From: Bert Gunter <bgunter.4567 at gmail.com> Sent: 24 May 2018 16:04 To: Ioanna Ioannou Cc:

This is one of those instances where a less superficial knowledge of R's technical details comes in really handy. What you need to do is convert the data frame to a single (numeric) vector for, e.g. a matrix() call. This can be easily done by noting that a data frame is also a list and using do.call(): ## imp is the data frame: do.call(c,imp) X11 X12 X13 X14 X15 X16 X17 X18 X19

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]]

Hello all, I would appreciate your thoughts on a seemingly simple problem. I have a database, where each row represent a single record. I want to aggregate this database so I use the aggregate command : D<-read.csv("C:\\Users\\test.csv") attach(D) by1<-factor(Class) by2<-factor(X) W<-aggregate(x=Count,by=list(by1,by2),FUN="sum") The results I

Hello everyone, I want to transform a data.frame into an array (lets call it mydata), where: mydata[[1]] is the first imputed dataset...and for each mydata[[d]], the first p columns are covariates X, and the last one is the outcome Y. Lets assume a simple data.frame: Imputed = data.frame( X1 = c(1,2,1,2,1,2,1,2, 1,2,1,2,1,2,1,2), X2 =

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 <-

Hello all, I have data in the form of a table: X Y1 Y2 0.1 3 2 0.2 2 1 And I would like to transform in the form: X Y 0.1 Y1 0.1 Y1 0.1 Y1 0.1 Y2 0.1 Y2 0.2 Y1 0.2 Y1 0.2 Y2 Any ideas how? Thanks in advance, IOanna [[alternative HTML version deleted]]

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

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(

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

Hello, I run a linear regression I get the summary, e.g.: > summary(lm.r) Call: lm(formula = signal ~ conc) Residuals: 1 2 3 4 5 0.4 -1.0 1.6 -1.8 0.8 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 3.60000 1.23288 2.92 0.0615 . conc 1.94000 0.05033

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 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, Is there any chance you will merge the suggested patch? Thanks, Jo On Thu, Apr 18, 2019 at 2:01 PM Richard W.M. Jones <rjones@redhat.com> wrote: > On Thu, Apr 18, 2019 at 12:17:18PM +0100, Ioanna Alifieraki wrote: > > I had tried this approach, to add > /etc/dhcp/dhclient-enter-hooks.d/resolved > > to excludefiles, however it didn't work. > > As far as I

Hello, I am trying to perform a logistic regression using counts. For example: cedegren <- read.table("http://www.cloudstat.org/index.php?do=/attachment/download/id_95 /", header=T) attach(cedegren) ced.del <- cbind(sDel, sNoDel) ced.logr <- glm(ced.del ~ cat + follows + factor(class), family=binomial("logit")) This works. However, if I change the family to

Hello, A very simple question but I am stuck. I have an excel file each row is an address. However, I cannot make geocode read each line and come up with the latitude longitude. Could you please correct my code? library(ggmap) X<-c (2 Afxentiou Ampelokipi Thessaloniki Greece, 2 Afxentiou Ampelokipi Thessaloniki Greece, 4 Afxentiou Ampelokipi Thessaloniki Greece, 55 Agathonos

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

I had tried this approach, to add /etc/dhcp/dhclient-enter-hooks.d/resolved to excludefiles, however it didn't work. As far as I know, this hook is included in the base image and according to [1], the current implementation does not apply excludefiles to the base image. Jo [1] https://github.com/libguestfs/supermin/blob/b2401285cd3e3d42006fc164ef1f046cc35a50c4/src/mode_build.ml#L137 On