similar to: KernSmooth: bkde and dpik bandwidth questions

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.

Hi there and thanks in advance. Nowadays 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) >

Any advice when to use denstity() and when the KernSmooth package bkde() to smooth a histogram? No specific problem to use either one, but I'm curious why there are two so similar implementations. Thanks! mario -- Ing. Mario Valle Data Analysis and Visualization Group | http://www.cscs.ch/~mvalle Swiss National Supercomputing Centre (CSCS) | Tel: +41 (91) 610.82.60 v.

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

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]]

Hi, I was using a density estimation function as follows: > est <- KernSmooth::bkde(x3, bandwidth=10) When setting bandwidth less than 5, I got the error "longer object length, is not a multiple of shorter object length in: kappa * gcounts ". I wonder if there is anybody who can explain the error for me? Thanks! Hui

Hi, I want to fit a kernel density estimator by bkde of library KernSmooth. I need only the density value at the point 0. I do not understand the following behaviour: > q <- rnorm(100) > bkq <- bkde(q, bandwidth=0.11, gridsize=1, range.x=c(0,0)) Error in 0:L : NA/NaN argument > bkq <- bkde(q, bandwidth=0.11, gridsize=1, range.x=c(-1,1)) > bkq $x [1] -1 $y [1] NA > bkq

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]]

Hi I hope this is going to the right place. I am trying to write a program which uses KernSmooth library to estimate mutual information between two time series at various different lags. At the moment it’s producing negative values, which is supposed to be impossible (something is fishy). I am summing across one row of the matrix to get p(value is in bin x) and summing across the columns to get

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

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

On 27 April 2017 at 12:01, Johannes Ranke wrote: | | > so it seems to me this must affect all packages in Debian sid that were | > built before the release of R 3.4.0! | | or rather before 14 April 2017, which is when R from revision r72510 was | uploaded to sid as pre-release candidate. Another example with KernSmooth: > library(KernSmooth) KernSmooth 2.23 loaded Copyright

Am Dienstag, 25. April 2017, 11:21:31 schrieb Dirk Eddelbuettel: > On 25 April 2017 at 16:11, Johannes Ranke wrote: > | This looks similar to what I got this morning when I tested my > | (unreleased) > | backport of R 3.4.0 to Debian jessie. My test was > | > | library(MASS) > | example(rlm) > | > | and there was an object that was not found. I am on a train on the way

There are 4 sets of array, each have 2 dimension data:x,y. And these data comes from bkde. I tried to plot them in one figure, but details of some lines, like peak and where it locate, have diminished since one set of array have fairly high y value.And another array have lots of y value near zero, like 1e-20, 1e-10, like a long tail, while the highest y value of these arrays is 1e-4. Does R have

Full_Name: Nuno Monteiro Version: 2.3.1 OS: Windows XP HE Submission from: (NULL) (84.9.38.207) I'm using the FEAR library to perform Data Envelopment analysis with a 36,000 obs dataset. The function dea is working fine but then when I try to use the boot.sw98 to come up with some sensitivity analysis I get the following error:

Hi, I have a vector or random variables and I'm estimating the density using "bkde" function in the KernSmooth package. The out put contains two vectors (x and y), and the R documentation calls y as the density estimates, but my y-values are not exact density etstimates (since these are numbers larger than 1)! what is y here? Is it possible to get the true estimated density at each

There is a series of data contains time in fixed step and energy varying with time, how to test its periodicity?In R, it seems there is no direct tools since I have search the R manual with periodic and I have not found any related topic. Thanks a lot

Dear R helpers I am having recovery rates as given below and I am trying to estimate the Loss Given Default (LGD) and for this I am using Kernel Density estimation method. recovery_rates = c(0.61,0.12,0.10,0.68,0.87,0.19,0.84,0.81,0.87,0.54,0.08,0.65,0.91, 0.56,0.52,0.30,0.41,0.24,0.66,0.35,0.36,0.64,0.55,0.43,0.36,0.28,0.89,0.11,0.23,0.07,

Hello, I wanted to know if there is a simple way of getting the inverse cdf for a KDE estimate of a density (using the ks or KernSmooth packages) in R ? The method I'm using now is to perform a numerical integration of the pdf to get the cdf and then doing a search for the desired probablity value, which is highly inefficient and very slow. Thanks, -fj [[alternative HTML version deleted]]

Hello, I am trying to get the output from the numerical simulation of a system of ordinary differential equations for a range of values for three parameters. I am using the ode() function (deSolve package) to run the numerical simulation and apply() to run the simulation function for each set of parameter values. I am having trouble getting the apply() function to work. Here is an