similar to: Asking help for finding the highest density region

To whom it may concern. As I would like to analyse some array data I was keen on downloading the lumi package that depends obviously on hdrcde that is not available for r 2.12.1. I did not find instructions to solve or circumvent this problem. Installing hdrcde by hand did not work either. It was not detected by > (.packages(all.available=TRUE)) if installed in the R library. Thanks Hermann

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

Dear R-help listers, I want to add 95% confidential interval as vertical lines to x axe in density plot. I have found the library(hdrcde) can do this work, but I do not know how to handle functions of this library when I used ggplot2 to draw the graph. Thank you in advance. The data and codes followed: # dummy data factor<-rep(c("Alice","Jone","Mike"),each=100)

Dear Listers, I am drawing a plot of two density curves, for male and female incomes. I would like to shade/hatch/color (whatever) the areas under the curves which are distinctive for each gender. This is the code I have tried so far: m <- density(topmal.d$y, bw = "sj") f <- density(topfem.d$y, bw = "sj") par(mfrow = c(1,1)) plot(x = c(0,400), y = c(0,0.02), type =

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

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

Hi all, I would like to include a function that I have made by modifying an existing R function (bw.SJ and corresponding code in bandwidths.c). The header of bandwidths.c states: /* * R : A Computer Language for Statistical Data Analysis * bandwidth.c by W. N. Venables and B. D. Ripley Copyright (C) 1994-2001 * Copyright (C) 2012 The R Core Team * * This program is free software; you

Hello, I recently bought a new Macbook Pro and installed R via a disk image from an older computer - it seems to work fine. I then installed the package "siar", tried to load it via the library command and received the following messages (note the "mvtnorm" package did not appear to load correctly): trying URL

Dear All,   could you please confirm (or disconfimr, and then please explain:-)) my understanding of the results generated by the following code:   hdr.den(rnorm(200,55,3))   result:           [,1]     [,2] 99% 47.07170 63.26864 95% 48.83670 61.55108 50% 53.04884 57.37916   the way I am interpreting the results is that in this normally distributed data set with the mean of 55 and SD of 3:   1. 99%

Hi all, I have a question regarding the density function which gives the kernel density estimator. I want to decide the bandwidth when using gaussian kernel, given a set of observations. I am not familiar with different methods for bandwidth determination. Below are the different ways in R on deciding the bandwidth. Can anyone give an idea on which ones are preferred. Also, how can I take

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

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 <-

Estimate region of highest probabilty density Dear R-community I have data consisting of x and y. To each pair (x,y) a z value (weight) is assigned. With kde2d I can estimate the densities on a regular grid and based on this make a contour plot (not considering the z-values). According to an earlier post in the list I adjusted the kde2d to kde2d.weighted (see code below) to estimate the

I'm trying to shade part of a density plot. The code I'm trying (using the Old Faithful data as an example) is something like this: # The Old Faithful geyser data data(faithful) d <- density(faithful$eruptions, bw = "sj") plot(d) polygon(d[d$x>4], col = "wheat") I expected that the part of the curve to the right of 4 on the x axis should be shaded, but nothing

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

On 26 September 2010 18:56, Nathan Jeffords <blunted2night at gmail.com> wrote: > The syntax for the invoke instruction is a little misleading. %x is a value > that is being generated by the instruction, not passed to is. It is no > different in that regard as to say '%x = call @eh.exception ...'. Since you > don't specify the type in that type of assignment, I chose

I did a CentOS 4.4 fresh server install. Using it to run Squid. Named is also running but I get this error. [root at sj ~]# /etc/init.d/named status rndc: connection to remote host closed This may indicate that the remote server is using an older version of the command protocol, this host is not authorized to connect, or the key is invalid. [root at sj ~]# /etc/init.d/named restart Stopping

Dear R-ians, I'm looking for a computational simplified formula to calculate a measure for heterogeneity (let's say H ): H = sqrt [ (Si (Sj (Xi - Xj)?? ) ) /n ] where: sqrt = square root Si = summation over i (= 0 to n) Sj = summation over j (= 0 to n) Xi = element of X with index i Xj = element of X with index j I can simplify the formula to: H = sqrt [ ( 2 * n * Si (Xi) - 2 Si (Sj

Hi Guys Im using Nokia 6680 to connect to dovecot (dovecot-1.0.b7_1 from FreeBSD ports) Where ever it trying to login it failed despite it works well with PC clients. * OK [CAPABILITY IMAP4rev1 SORT THREAD=REFERENCES MULTIAPPEND UNSELECT LITERAL+ IDLE CHILDREN NAMESPACE LOGIN-REFERRALS AUTH=PLAIN AUTH=LOGIN] Dovecot ready. 1 CAPABILITY * CAPABILITY IMAP4rev1 SORT THREAD=REFERENCES MULTIAPPEND