similar to: percent rank by an index key?

I'm not sure I'm barking up the right tree here, but would I need to make use of groups to plot two separate datasets within ONE panel in xyplot? The desired end result is a single xy plot of two separate (but similar in values and ranges). Full code follows, xyplot code at bottom #########Determine Frequencies ##########coastal_slope #needs the maptools package to read ESRI grid

Hi, I have a vector with values: x <- rnorm(1000, 5, 2) and one single value: y <- 6.2 now I would like to know the percent rank of y based on the 'population'-vector x. Is there a convenient function that calculates the percent rank of a y for the given vector x? thanks!

Hi, It is not that clear. If VAR1 is a match between columns AB001A, AB0002A, VAR2? between AB001A, AB362 and VAR3 between AB0002A and AB362: Also, I assume row8 match would be taken as 1. dat1<- read.table(text=" ? S.No AB001A AB0002A AB362 ?? 1?? -/-??????? C/C?? A/A??????????????????????? ??? 2?? C/C??????? C/C?? A/A??????????????????????? ??? 3?? C/C??????? C/C??

Hello, I am using the mail_crypt plugin with Dovecot 2.3 and have issues trying to use a mail crypt private password which contains a percent "%" character as you can see below: $ doveadm -o plugin/mail_crypt_private_password=SomethingWith\%Percent mailbox cryptokey generate -u email at domain.tld -URf doveadm(email at domain.tld): Error: Failed to expand plugin setting

I have not been able to find a way to do dense rank in R Here is an example of what I need rank() gives the following 5 rank 1 7 rank 2 7 rank 2 9 *rank 4* but I want 5 rank 1 7 rank 2 7 rank 2 9 *rank 3* * * thanks SS [[alternative HTML version deleted]]

I have searched this forum with keywords contour and percent, it only give one irrelevent result. My problems is how to plot contour in percent. In my figure, I have use kde2d to generate density of an array with two dimension point. Using image and contour could plot it. But the line contour generated represent absolute value of population, not how much pecent point within this cycle. So, i there

how do I check the rank of a matrix ? say A= 1 0 0 0 1 0 then rank(A)=2 what is this function? thanks I did try help.search("rank"), but all the returned help information seem irrelevant to what I want. I would like to know how people search for help information like this. rank(base) Sample Ranks SignRank(stats) Distribution of the

Hi, I have noticed different rank values calculated by qr() depending on LAPACK parameter. When it is FALSE (default) a true rank is estimated and returned. Unfortunately, when LAPACK is set to TRUE, the min(nrow(A), ncol(A)) is returned which is only occasionally a true rank. Would not it be more consistent to replace the rank in the latter case by something based on the following pseudo code ?

Full_Name: Stella David Version: 2.1.0 OS: mingw32 Submission from: (NULL) (137.250.161.136) It seems that rank doesn't work right on vectors containing negative values. If the negative value is the first component or there are only two components, it works, but if the negative value is somewhere in the middle there's a problem. Here are my examples: > # wrong: > x<-

Hallo Anupam I do not see much difference in ggplot or lattice, they seems to me provide almost identical results when removing theme part from ggplot. library(ggplot2) library(lattice) ggplot(TrialData4, aes(x=Income, y=Percent, group=Measure)) + geom_point() + geom_line() + facet_wrap(~Measure) xyplot(Percent ~ Income | Measure, TrialData4, type = "o", pch = 16, as.table =

Le 23/01/2018 ? 08:47, Martin Maechler a ?crit?: >>>>>> Serguei Sokol <sokol at insa-toulouse.fr> >>>>>> on Mon, 22 Jan 2018 17:57:47 +0100 writes: > > Le 22/01/2018 ? 17:40, Keith O'Hara a ?crit?: > >> This behavior is noted in the qr documentation, no? > >> > >> rank - the rank of x as

In some contexts, I find the current behavior of rank() very `suboptimal'. We have the argument na.last = {TRUE | FALSE | NA } where the first two cases treating NAs (almost) as if they were == +Inf or == -Inf whereas the 3rd case just drops NAs. For the typical ``Rank Transformation'' that is recommended in EDA in several contexts, I would however want something else, namely keep

Does anyone know why the two rank functions gives different results? I need to use the rank function in a "for" loop, so the sequence to be ranked is given values in the form of part (1). How can I use assignment like in part (1) to get correct ranks as in part (2)? Thank You Part (1) i<-1.94 b<-0.95-i c<-1.73-i d<-2.62-i y<-c(0.68,0.95,b,c,d) y 0.68 0.95 -0.99

Thanks! You are correct, the graphs look very similar, except ggplot is scaling the text font to make it more readable. Is there a way to scale down the x-axis labels, so they are readable? On Fri, 7 Jul 2023 at 12:02, PIKAL Petr <petr.pikal at precheza.cz> wrote: > Hallo Anupam > > I do not see much difference in ggplot or lattice, they seems to me > provide almost identical

Dear List, I am trying include a lunar variable in a model and am having problems figuring out the correct way to include it. I want to convert the percent lunar illumination (fraction of moon showing) to a combination of sin and cos variables to account for the periodic nature of the lunar cycle. Would someone let me know if I am doing this correctly? I have included the first 20 variables

Hi All - I have been using the windrose function found in the circular library to create great looking windroses.  But the dashed, circular percent interval lines that indicate the frequency at which each "pedal" occurs are not evenly spaced (the corresponding parameter is "cir.ind").  That is, the 5% interval closest to the heart of the windrose is wider than the 5-10 chuck,

Could someone give me an idea on how to do rolling ranking, i.e. rank in the moving window of last 100 numbers in a long vector? I tried naive solution like roll.rank<-function(v, len){ r<-numeric(length(v)-len+1) for(i in len:length(v)) r[i-len+1]<-rank(v[(i-len+1):i])[len] r } However, it turns out pretty slow even on my rather able Linux box. For

Greetings. There seems to be a problem with the P-value computation in the cor.test with method="spearman". In R1.8.0 (MS Windows) I seem to be getting intermittently nonsense P-values, but the rho's are OK. I can get this reproducibly with the toy example attached where the first use is OK and subsequent calls with the same data give nonsense. (I have also seen the problem

I don't know the difference between rank and order.For example: > x=c(10,30,30,20,10,20) > x[rank(x,ties.method="first")] [1] 10 10 20 30 30 20 > x[order(x)] [1] 10 10 20 20 30 30 the result is quite different, x[rank(x,ties.method="first")] [1] 10 10 20 30 30 20 It is not sorted,why? -- View this message in context:

Hello, I am trying to get the 'rank' function to work for me, but not sure what I am doing wrong. Please help. I ran the following commands: data = read.table("test1.csv", head=T, as.is=T, na.string=".", row.nam=NULL) X1 = as.factor(data[[3]]) X2 = as.factor(data[[4]]) X3 = as.factor(data[[5]]) Y = data[[2]] model = lm(Y ~ X1*X2*X3, na.action = na.exclude) fmodel =