similar to: Help with packages (methods, stats, stats4)

Hi, Did you try install.packages('stats'). Let we know about your Sys.info() Karim On Fri, Jan 12, 2018 at 5:37 PM, imane hajar <imane.chafiki.fst at gmail.com> wrote: > hello , > > i am so sorry , i figure it out. > > im sending this msj to the moderator to stop the approval of the mail . > > have a good day. > > > 2018-01-12 15:42 GMT+00:00 imane

Yes, You are right. I mean install.packages('DVstats'). Actually, it seems that DVstats does not have maintainer https://github.com/USGS-R/DVstats Karim On Fri, Jan 12, 2018 at 7:20 PM, Duncan Murdoch <murdoch.duncan at gmail.com> wrote: > On 12/01/2018 1:11 PM, Karim Mezhoud wrote: > >> Hi, >> Did you try install.packages('stats'). >> > > That

On 12/01/2018 1:11 PM, Karim Mezhoud wrote: > Hi, > Did you try install.packages('stats'). That will not work, as stats is a base package. It comes with R, and can't be changed. The stats package should never be missing in a proper install of R. Duncan Murdoch > Let we know about your Sys.info() > Karim > > On Fri, Jan 12, 2018 at 5:37 PM, imane hajar

hello , i am so sorry , i figure it out. im sending this msj to the moderator to stop the approval of the mail . have a good day. 2018-01-12 15:42 GMT+00:00 imane hajar <imane.chafiki.fst at gmail.com>: > hello, > Can you please give me a hand with this problem,well i can't install > these packages: > - stats > - methods > - stats4 > > when i tried the

On 12/01/2018 1:25 PM, Karim Mezhoud wrote: > Yes, > You are right. I mean > install.packages('DVstats'). That won't work either, because DVstats is not on CRAN. > Actually, it seems that DVstats does not have maintainer > https://github.com/USGS-R/DVstats You can try install.packages("devtools") # if not already installed...

1. Unless there is a good reason not to, please always cc the list. As you note, I may misunderstand or just be too stupid, so you increase your chance of getting a good answer by ccing them, which I have done here 2. It looks like you need to install the multcomp package. Have you? Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and

Hi Bert, I am sorry to bother you on weekend. I am still struggling on defining a correct function. I first defined the function RFS (see below), then run it by provide the two argument. m52.2cluster <-RFS(inputfile =allinfo_m52, N=2 ) I do not get error message, but no figure displays on screen. I do not know what is going on. Can you help me a little more on this issue? Thank you,

Hi Richard, Thank you so much!! I understand the problem now, I assign a name to the "ggsurvplot" object and then add print(fig) at bottom of function definition, now figure gets printed on screen. Ding # function to generate RFS curves RFS <- function( inputfile, N ) { cluster<- survfit(Surv(RFS_days2, OV_Had_a_Recurrence_CODE) ~ clusters, data =

FAQ 7.22 You must print a ggplot object, for example with print(m52.2cluster) For the FAQ, run the line system.file("../../doc/FAQ") in R on your computer. Open up the resulting filepath in your favorite editor and scroll down to 7.22 On Sun, Jan 14, 2018 at 4:21 PM, Ding, Yuan Chun <ycding at coh.org> wrote: > Hi Bert, > > I am sorry to bother you on weekend. >

That is certainly OK, but you can also just use print(ggsurvplot(...)) as your final statement. out <- RFS( ...) would then return the ggsurvplot object *and* graph it. Any good R tutorial or a web search will provide more details on function returns, which you might find useful. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and

Thank you, your suggestion is simpler and logically better. I had impression that the last object in a function gets returned, so I did not add the print function at the bottom line of the function definition. Returning an object and graph the object are different process, I am a beginner for writing R function and need to find a good guide source about writing R functions. If you know a good

HI R users, I construct dendrogram tree and cut the tree into different clusters, then generate survival curves by the following three functions. All variables are included in an inputfile. Can you help me to consolidate the following three function into one functions? I thought about using if else function, but not sure how to do it. Thank you, Ding # function to generate RFS RFS2cluster

Hi, I wantto use 'mle' function in R on linux. As I see its been integrated into the stats4 package. Am I correct ? If yes, Can anyone suggest how to install the stats4 package to be able to run 'mle' function in R on linux ? Otherwise how to sort out this problem ? Thanks Himanshu [[alternative HTML version deleted]]

Hi Bert, Thank you, yes, you are right. I want to consolidate the three functions into one functions by adding more arguments, adding flexibility to accommodate the number of clusters or the number of Kaplan Meier curves generated in one figure. So, I just need to define one function. Thanks, Ding From: Bert Gunter [mailto:bgunter.4567 at gmail.com] Sent: Sunday, January 14, 2018 9:50 AM

Hi everyone! I am using the mle {stats4} to estimate the parameters of distributions by MLE method. I have a problem with the examples they provided with the mle{stats4} html files. Please check the example and my question below! *Here is the mle html help file * http://stat.ethz.ch/R-manual/R-devel/library/stats4/html/mle.html http://stat.ethz.ch/R-manual/R-devel/library/stats4/html/mle.html

Dear developers, the implementation of S4 generics for existing S3 ones in the base package is concerned to be a threat to quick startup times [1]. But since S4 is promoted, and S3/S4 interoperability a pain when package developing [2], are there efforts to improve the situation? E.g. an S3 free system, etc. A good thing [2] is the package 'stats4', including some setGeneric calls (e.g.

Hi! This is a repost of an earlier message (with a clearer example demonstrating the problem I ran into). If you run the mle example in stats4 library(stats4) x <- 0:10 y <- c(26, 17, 13, 12, 20, 5, 9, 8, 5, 4, 8) ll <- function(ymax=15, xhalf=6) -sum(stats::dpois(y, lambda=ymax/(1+x/xhalf), log=TRUE)) (fit <- mle(ll)) plot(profile(fit),

I am using mle as a wrapper from optim( ). How would I extract the convergence code, to know that optim( ) converged properly? Thanks, Stephen Collins, MPP | Analyst Global Strategy | Aon Benfield [[alternative HTML version deleted]]

With the exception of "L-BFGS-B", all of the other optim() methods return the value of the function when they are given a trivial function (i.e., one with no variable arguments) to optimize. I don't think this is a "bug" in L-BFGS-B (more like a response to an undefined condition), but it leads to a bug in stats4::mle -- a spurious error saying that a better fit has been

Hi, We're using stats4 for a logistic regression. The code is chdreg.logit2 <- glm(chd ~ age + sex, family = binomial) summary(chdreg.logit2) oddsratios <- coef(chdreg.logit2) exp(oddsratios) # Calculate model predicted values pred <- predict(chdreg.logit2,type="response") The glm part runs fine, and up to now so has the predict function. However, now we're