similar to: M-estimator R function question

Hi, The following code, from Angelo Canty article on line "Resampling Methods in R: the boot Package, 2002", works fine for Angelo Canty using R 2.6.0 on Windows XP. It also works for me using R 1.2.1 and S-PLUS 2000 on Windows XP after installing the S-PLUS bootstrap library, with slight differences in my outputs. > library(boot) > library(survival) >

Hi! I tested two different implementations of the robust MCD estimator: cov.mcd from the MASS package and covMcd from the rrcov package. Tests were done on the hbk dataset included in the rrcov package. Unfortunately I get quite differing results -- so the question is whether this differences are justified or an error on my side or a bug? Here is, what I did: > require(MASS) >

This is my first post requesting help to this mailing list. I am new to R. My apologies for any breach in posting etiquette. I am new to this language and just learning my way around. I am attempting to run some sample code and and am confused by the error message: Loading required package: rrcov Error in fitNorm2(fdat[, "FSC-H"], fdat[, "SSC-H"], scalefac = ScaleFactor) :

Hello, I'm using the R-2.13.1 version in Windows and I'm trying to do a robust Pca with the following: x<-matrix(0.5,30,30) library("rrcov") y<-PcaCov(x) The following error occurs: Error: diff(sv)<0 ist not all TRUE The same error occurs with the other functions. What does this mean and how can I perform the robust PCA with these functions by using a quadratic

[Env: R 2.14.2 / Win Xp] In the script below, I want to select some variables from rrcov::OsloTransect, delete cases with any missing data, and subset the data frame Oslo to remove cases for two levels of the factor litho that occur with low frequency. The checks I run on my new data frame Oslo look OK, but I when I try to fit a multivariate linear model with lm(), I am getting an error:

Hello an update about my question: I worked out the following solution (with the package "dplyr") library(dplyr) mydf%>% mutate(speed_vehicles=n_vehicles*mydf$speed) %>% group_by(date_time,type) %>% summarise( sum_n_times_speed=sum(speed_vehicles), n_vehicles=sum(n_vehicles), vel=sum(speed_vehicles)/sum(n_vehicles) ) In fact I was hoping to manage everything in a

Hello to R people Does anybody know to calculate exact logistic regression in R? Does such option exist anywhere? Surprisingly, could not find it using search engine. It is hard to believe, however, that such useful function is not implemented in R yet? Could you help, please Thank you Denis

hi all I have this dataframe (created as a reproducible example) mydf<-structure(list(date_time = structure(c(1508238000, 1508238000, 1508238000, 1508238000, 1508238000, 1508238000, 1508238000), class = c("POSIXct", "POSIXt"), tzone = ""), direction = structure(c(1L, 1L, 1L, 1L, 2L, 2L, 2L), .Label = c("A", "B"), class =

When I install an R package with cpp codes such as rrcov via CRAN (under R 3.1.1, using no Makevars file and under Ubuntu 14.04 using GCC 4.8), the cpp code is compiled with the -o3 flag (in fact, looking at the Makeconf file this seem to again be the default since R 3.1.1) But when I install my own package via CRAN it is compiled with the -o2 flag. My questions are what is causing my

Hi, I want to do a 2 sample hotelling's test but i can't figure out how. When i type T2.test it says there is no such test and when i tried library(rrcov) it says there is no such program. Cheers. -- View this message in context: http://r.789695.n4.nabble.com/How-to-do-Hotelling-s-t2-test-tp4128748p4128748.html Sent from the R help mailing list archive at Nabble.com.

Dear Massimo, It seems straightforward to use weighted.mean() in a dplyr context library(dplyr) mydf %>% group_by(date_time, type) %>% summarise(vel = weighted.mean(speed, n_vehicles)) Best regards, ir. Thierry Onkelinx Statisticus / Statistician Vlaamse Overheid / Government of Flanders INSTITUUT VOOR NATUUR- EN BOSONDERZOEK / RESEARCH INSTITUTE FOR NATURE AND FOREST Team

On 1/20/20 4:26 AM, Martin Maechler wrote: > Coming late here -- after enjoying a proper weekend ;-) -- > I have been agreeing (with Spencer, IIUC) on this for a long > time (~ 3 yrs, or more?), namely that I've come to see it as a > "design bug" that rpois() {and similar} must return return typeof() "integer". > > More strongly, I'm actually pretty

Hello, Try the following. icol <- which(grepl("flag", names(mydf))) mydf[icol] <- lapply(mydf[icol], function(x){ is.na(x) <- x == 0 x }) mydf # A A_flag B B_flag #1 8 10 5 12 #2 7 NA 6 9 #3 10 1 2 NA #4 1 NA 1 5 #5 5 2 0 NA Hope this helps, Rui Barradas On 11/22/2017 10:34 AM, Massimo Bressan

Dear all, The other day I was reading this post [1] that slightly surprised me: "To reject the null of no correlation, an hypothsis test based on the normal distribution. If normality is not the base assumption your working from then p-values, significance tests and conf. intervals dont mean much (the value of the coefficient is not reliable) " (BOB SAMOHYL). To me this implied that in

I haven't seen this cryptic warning before: > update.views('Robust') Warning message: In update.views("Robust") : The following packages are not available: covRobust, distr, FRB, MASS, mblm, multinomRob, mvoutlier, quantreg, RandVar, rgam, RobAStBase, robfilter, RobLox, RobRex, robust, RobustAFT, robustbase, ROptEst, ROptRegTS, rrcov, sandwich, wle >

Dear R-helpers, First, double apologies because the question is not directly related to R, and also probably quite simple. I have observed (with many data) that given 2 series X and Y cor(X,Y) and cor(log(X), log(Y)) differs only very slightly. I suspect this is because log(x) is monotonous, ... but I am unable to demonstrate it. (perhaps it is also wrong ?). Would somebody here be able and

Ugh, sounds like competing priorities. * maintain type consistency * minimize storage (= current version, since 3.0.0) * maximize utility for large lambda (= proposed change) * keep user interface, and code, simple (e.g., it would be easy enough to add a switch that provided user control of int vs double return value) * backward compatibility On 2020-01-20 12:33 p.m., Martin Maechler

Can anyone please help, I can't tell why it will not connect. I do not know how to read this debug file to were it is wrong. Thanks Sip read: REGISTER sip:192.168.1.101 SIP/2.0 Via: SIP/2.0/UDP 192.168.1.100:9082 From: <sip:2203@192.168.1.101>;tag=97442d5b-75b7-4e23-9021-b8605797eb56 To: <sip:2203@192.168.1.101> Call-ID: ea352d6f-a879-4db6-a361-365487a20d4a@192.168.1.100 CSeq: 1

Hi Thanks for working example. you could use split/ lapply approach, however it is probably not much better than dplyr method. sapply(split(mydf, mydf$type), function(speed, n_vehicles) sum(mydf$speed*mydf$n_vehicles)/sum(mydf$n_vehicles)) gives you averages aggregate(mydf$n_vehicles, list(mydf$type), sum)$x gives you sums Cheers Petr > -----Original Message----- > From: R-help

Hi, I have a strange package installation problem after update to R 2.11.0 on Fedora Core 12. A colleague of mine with the very same Fedora and R versions doesn't have this problem, while logging on to his computer but installing from my settings and into my local library path also shows the problem, so it seems to be related to some of my environment settings. Installation of several