similar to: Including modified R source code in a package

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 tried to modify the R function bw.SJ (from the stats package) for my own use. But if I just get the source code and run directly (without any modification), it can no longer find some key functions called within it. I understand this has something to do with searching path which I do not understand well. Can anyone tell me how to modify the source code of an R function and still make it part of

I tried to modify the R function bw.SJ (from the stats package) for my own use. But if I just get the source code and run directly (without any modification), it can no longer find some key functions called within it. I understand this has something to do with searching path which I do not understand well. Can anyone tell me how to modify the source code of an R function and still make it part of

Hello dear R-helpers, I'm working with R-2.15.2 on Windows 7 OS. I'm stucked with a merge of two data frames by characters. In each data frame I got two different list of names, that is my main-key to be merged. To figure out what I'm saying, I build up a modified "?merge" example, with errors by purpose: # Data for authors: authors <- data.frame( surname =

I am using the package hdrcde to get the highest density region. I have the data from an unknown distribution. And I used the subroutine hdr from the package to get the highest density region. But I always got a error message. I do not know why. Who can help?Thanks! The codes look like this: j is the data set, > hdr(j) Error in bw.SJ(x) : no solution in the specified range of bandwidths

On Tue, Oct 6, 2015 at 4:58 PM, Adrian Du?a <dusa.adrian at unibuc.ro> wrote: > Hi Gabriel, > > On Tue, Oct 6, 2015 at 10:59 PM, Gabriel Becker <gmbecker at ucdavis.edu> > wrote: > >> [...] >> >> At the very least, this is seems to be a flagrant violation of the >> *spirit* of the CRAN policy, which AFAIK is intended to enforce >>

Hi, I am wondering if the kde2d 2-D kernel density estimation function in the MASS package can take into account the effect of correlations between the variables. I couldn't find any achieved information on this issue. Unfortunately, I don't have the 2002 edition of Modern Applied Statistics with S by Venables and Ripley in case it was described there. Thanks in advance. Adam

While termplot is under discussion, here's another proposal. I'd like to change the default for partial.resid to TRUE, and for smooth to panel.smooth. I'd be surprised if those changes were to break existing code. John Maindonald email: john.maindonald at anu.edu.au phone : +61 2 (6125)3473 fax : +61 2(6125)5549 Centre for Mathematics & Its Applications, Room

Adrian, I am not on the CRAN or R-core teams, so the following is my own view, but... > library(QCA) > > Users are encouraged to cite this package as: > > Dusa, Adrian (2015). QCA: Qualitative Comparative Analysis. R Package > Version 1.2-0, > URL: http://cran.r-project.org/package=QCA > > This is just an encouragement, not a requirement, and the official citation

I have a problem moving from multistratum aov analysis to lmer. My dataset has observations of ampl at 4 levels of gapf and 2 levels of bl on 6 subjects levels VP, with 2 replicates wg each, and is balanced. Here is the summary of this set with aov: >> summary(aov(ampl~gapf*bl+Error(VP/(bl*gapf)),hframe2)) > >Error: VP > Df Sum Sq Mean Sq F value Pr(>F) >Residuals

Adrian, Responses inline On Tue, Oct 6, 2015 at 1:58 PM, Adrian Du?a <dusa.adrian at unibuc.ro> wrote: > Hi Gabriel, > > On Tue, Oct 6, 2015 at 10:59 PM, Gabriel Becker <gmbecker at ucdavis.edu> > wrote: > >> [...] >> >> At the very least, this is seems to be a flagrant violation of the >> *spirit* of the CRAN policy, which AFAIK is intended to

Hi, I am wondering if there is a simple way to fix the problem I am having. For unknown reason, I could not get the full name of the factors to be printed in the summary. I have tried to used summary.lm as well but the problem still persists. SJ$Weekday <-

Hi , Thanks greg , for pointing out the valuable resources for reference. I tried SJphone in a windows environment to connect to fwd and it worked fine(including (audio). Now have to do the same thing for linux(red hat 9 ) and hope the nat issue is resolved. Now i would like to connect asterisk to fwd and instead of the SJ phone connecting to fwd directly i would wish to connect through

I found writing the following default method the for the generic function "julian" causes R to crash. julian.default <- function(x, ...) { x <- as.Date(x) NextMethod("julian", x, ...) } Here is a test example > m <- as.Date("1972-09-27") + 0:10 > m [1] "1972-09-27" "1972-09-28" "1972-09-29"

Does anyone have, or has anyone ever considered making, a version of 'termplot' that allows the user to specify that all plots should have the same y-limits? This seems a natural thing to ask for, as the plots share a y-scale. If you don't have the same y-axes you can easily misread the comparative contributions of the different components. Notes: the current version of termplot

Does anyone have, or has anyone ever considered making, a version of 'termplot' that allows the user to specify that all plots should have the same y-limits? This seems a natural thing to ask for, as the plots share a y-scale. If you don't have the same y-axes you can easily misread the comparative contributions of the different components. Notes: the current version of termplot

I have two series of events over time and I want to construct a graph of the relative frequency/density of these events that allows their distributions to be sensibly compared. The events are the milestones items in my project on milestones in the history of data visualization [1], and I want to compare trends in Europe vs. North America. I decided to use a graph of two overlaid density

> I think we should get rid of source attributes completely, > since they are no longer needed, but your comment still > applies to source references. We should strip them when code > gets modified. > > Duncan Murdoch I would be very concerned about losing source attributes-- it would break a lot of my code :(! It's very useful to have a single portable R object that

Happy New Year to all, I am using RW0631 and WIN98. 1. The command DATA only works for the base library. 2. The following code on page 312 of Venables and Ripley 1997 sitka.lme <- lme(size~treat*ordered(Time),random=~1,cluster=~tree,data=Sitka, serial.structure="ar1.continuous",serial.covariate=~Time) produced the following error message Error in lme(size ~ treat *

Hi all, I'm trying to resolve a weird issue with SIP routing. I have a number of SIP trunks, from a selection of providers, all of which are registered in sip.conf: [general] context=default allowguest=no allowoverlap=no udpbindaddr=0.0.0.0 tcpenable=yes tcpbindaddr=0.0.0.0 transport=udp bindport=15060 srvlookup=yes allowsubscribe=yes