search for: dpik

Thank you for your reply. I know the x in dpik() means the vector. But I don't know how to import into c() with a huge metadata (>1000). Following is my some try, and the h is: [1] 0.001180569, which seems to be feasible. x<-c(-0.00109349389485645,-0.00145304131152137,0.00023685387037116,0.00579094886320110,0.00032117330426379,0.003...

Hi, I have two separate questions relating to the KernSmooth package. I am using the dpik function from the KernSmooth package and receive the error Warning message: In kappam * Gcounts : longer object length is not a multiple of shorter object length I saw an earlier post , but the issue was using the bkde fxn and the person appeared to be using too small of a bandwidth....

...ys I am working on the plug-in bandwidth selection with R. Firstly, my 1010 data is the return rate from Yahoo Finance. Secondly, my code is following: > r=read.table("/Users/user/Desktop/research/a.txt",sep=",",header=TRUE) > x<-r[8:1010,] > library(KernSmooth) > dpik(x,scalest="minim",level=2L,kernel="normal",canonical=FALSE,gridsize=401L,range.x=range(x),truncate=TRUE) But the error happens like this: Error in Summary.factor(c(233L, 917L, 381L, 748L, 272L, 242L, 269L, 963L, : range not meaningful for factors I don't know what'...

Hi, I'm relatively new to R and R development, so please forgive me for any obvious errors. What I am trying to do is use the command dpik within the package KernSmooth to estimate bandwidth parameters for GPS telemetry data. I have been able to get this to work on a case by case basis without any problem, but would like to extend this so that I can batch process many different animals for pre-determined time periods (months of the y...

Epanechnikov kernel works if option canonical=TRUE, however it would be good to know why it does not for for canonical=FALSE (default). Sorry for craetaing maybe useless thread. Best regards, Ondra. [[alternative HTML version deleted]]

...numeric(100) mut<-numeric(lmax) jointplogp<-matrix(0,nrow=100,ncol=100) lh<-as.vector(datin[,1]) rh<-as.vector(datin[,2]) rhemb<-embed(rh,lmax) lhc<-lh[1:length(rhemb[,1])] for (i in 1:lmax) { rhc<-rhemb[,i] kd<-bkde2D(cbind(lhc,rhc),bandwidth=c(dpik(lhc),dpik(rhc)),gridsize=c(100,10 0),truncate=T) #2d kernel density estimate in 2 dimensions) kdmat<-as.matrix(kd$fhat) for (j in 1:100){ p<-sum(kdmat[j,]) lhplogp[j]<-p*log(p) } lhplogp[is.nan(lhplogp...

Hi, I am using the KernSmooth package to estimate nonparametrically bivariate density functions. However, it seems that the bandwidths (one for each co-ordinate direction) have to be selected manually. This does not apply for the univariate case, for which dpik (included in KernSmooth) uses up-to-date plug-in rules. Does anyone know about a package, or function, which estimates bandwidths for the BIVARIATE case, following, for instance, the plug-in methods suggested by Wand and Jones? I will appreciate your help a lot. Thanks, Emili References: W...

Hello, I've been using the KernSmooth package recently and think I have found a problem with it: after loading the library I can issue bkde(c(27,26,27), bandwidth=dpik(c(27,26,27)), range.x=c(4.4, 113.6), gridsize=128, truncate=T) and bkde returns an error. If I change the gridsize to 129 the function works perfectly. I have tried this on my Linux box, and on a nearby Solaris machine, both give an error (but not quite the same one). In case anyone is wondering...

Dear Sir/Madam; Would you please tell me what is the command that allows the estimation of the Kernel Density for some data. Thanks, Thami Rachidi [[alternative HTML version deleted]]

...,0.94,0.49,0.40,0.55,0.68,0.89,0.00,0.42,0.94,0.06,0.53,0.46,0.11,0.96, 0.41,0.69) I need to find out the bandwidth and I have two ways of doing it as # as per the stats package bw1 = bw.nrd0(recovery_rates)             #    which gives me bw1 = 0.1050780 # as per the KernSmooth package bw2 = dpik(recovery_rates)                    #    which gives bw2 = 0.1027932 I am bit confused which bandwidth is to be used. Is it that "statistics package" deal with univariate data while KernSmooth deals with multivariate data? Also, whenever I need to read some package, I download the respect...