search for: 24.4

Hi, There has been some recent work to improve the speed of the Message Authentication Codes (MACs) that are used in OpenSSH. The first improvement is a change from Markus Friedl to reuse the MAC context, rather than reinitialising it for every packet. This saves two calls to the underlying hash function (e.g. SHA1) for each packet. My tests found that this yielded at 12-16% speedup for bulk

Hi everyone, This is about documentation for the model.frame() page. The get_all_vars() function (added in R 2.5.0) is a great addition, but the behavior of its '...' argument is different from that of model.frame() with which it is documented and this creates ambiguity. The current docs read: \item{\dots}{further arguments such as \code{data}, \code{na.action}, \code{subset}. Any

Okay. Here is a modification that does four single line plots. at_df<-read.table(text= "Income MF MF_None MF_Equity MF_Debt MF_Hybrid Bank_None Bank_Current Bank_Savings Bank_NA $10 1 3.05 29.76 31.18 36.0 46.54 24.75 25.4 3.307 $25 2 2.29 28.79 32.64 36.27 54.01 24.4 18.7 2.891 $40 3 2.24 29.51 34.31 33.94 59.1 25.0 29 13.4 $75 4 1.71 28.90 35.65 33.74 62.17 24.61 11.48 1.746

Hi John: Thanks! Below is the data using your suggestion. I used "ggplot" to make a graph. I am not too happy with it. I am looking for something simpler and cleaner. Plot is attached. I also tried "lattice" package, but nothing got plotted with "xyplot" command, because it is looking for a numeric variable on x-axis. ggplot(TrialData4, aes(x=Income, y=Percent,

Thanks, Pikal and Jim. Yes, it has been a long time Jim. I hope you have been well. Pikal, thanks. Your solution may be close to what I want. I did not know that I was posting in HTML. I just copied the data from Excel and posted in the email in Gmail. The data is still in Excel, because I have not yet figured out what is a good way to organize it in R. I am posting it again below as text. These

Btw, I think "lattice" graphics will provide a better solution than "ggplot", because it puts appropriate (space saving) markers on the axes and does axes labels well. However, I cannot figure out how to do it in "lattice". On Thu, 6 Jul 2023 at 15:11, Anupam Tyagi <anuptyagi at gmail.com> wrote: > Hi John: > > Thanks! Below is the data using your

On Thu, 6 Jul 2023 at 15:21, Anupam Tyagi <anuptyagi at gmail.com> wrote: > > Btw, I think "lattice" graphics will provide a better solution than > "ggplot", because it puts appropriate (space saving) markers on the axes > and does axes labels well. However, I cannot figure out how to do it in > "lattice". You will need to convert Income to a

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 =

Anupa, I think your best bet with your data would be to tidy it up in Excel, read it into R using something like the readxl package and then supply some sample data is the dput() function. In the case of a large dataset something like dput(head(mydata, 100)) should supply the data we need. Just do dput(mydata) where *mydata* is your data. Copy the output and paste it here. On Thu, 29 Jun 2023

Hi - I'd like to construct and plot the percents by year in a small data set (d) that has values between 1988 and 2007. I'd like to have a breakpoint (buy no discontinuity) at 1996. Is there a better way to do this than in the code below? > d year percent se 1 1988 30.6 0.32 2 1989 31.5 0.31 3 1990 30.9 0.30 4 1991 30.6 0.28 5 1992 29.3 0.25 6 1994 30.3

Hi Anupam, Haven't heard from you in a long time. Perhaps you want something like this: at_df<-read.table(text= "Income MF MF_None MF_Equity MF_Debt MF_Hybrid Bank_None Bank_Current Bank_Savings Bank_NA $10 1 3.05 29.76 31.18 36.0 46.54 24.75 25.4 3.307 $25 2 2.29 28.79 32.64 36.27 54.01 24.4 18.7 2.891 $40 3 2.24 29.51 34.31 33.94 59.1 25.0 29 13.4 $75 4 1.71 28.90 35.65 33.74

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

Hi, I have a matrix of results of multiple 2x2 chi^2 tests, non- significant tests are marked as TRUE. Is there a function for grouping those variables in a similar way LSD.test from agricolae library does? I reviewed LSD.test's source but it's not helpful for me. This is my matrix: [,1] [,2] [,3] [,4] [,5] [,6] [,7] 1 TRUE FALSE TRUE TRUE TRUE FALSE TRUE 2 FALSE TRUE

Dear R-help mailing list,   Kindly help me out with this problem:   I have a dataset that is in the format below, ID  time  Y  Age 1  0     195  23.1 1  2    204  23.3 1  4   202    23.5 2  0  170    22.0 2  3   234   22.2 3  0  208   24.4 3  2  194  24 .7 3  3   204  24.9   I wish to remove all the measurements at time point 0 and convert them to a baseline variable as follows;    ID  time  Y 

Hello again, It appears that get_all_vars() incorrectly handles model formulae that use a right-hand side (rhs) matrix. For example, consider these two substantively identical models: # model using named variables mpg <- mtcars$mpg wt <- mtcars$wt hp <- mtcars$hp m1 <- lm(mpg ~ wt + hp) # model using matrix y <- mtcars$mpg x <- cbind(mtcars$wt, mtcars$hp) m2 <- lm(y ~ x)

Hi anyone coded up Stirling numbers in R? [I need unsigned Stirling numbers of the first kind] cheers Robin -- Robin Hankin Uncertainty Analyst National Oceanography Centre, Southampton European Way, Southampton SO14 3ZH, UK tel 023-8059-7743

Hello, I want to plot the following kind of data (percentage of respondents from a survey) that varies by Income into many small *line* graphs in a panel of graphs. I want to omit "No Answer" categories. I want to see how each one of the categories (percentages), "None", " Equity", etc. varies by Income. How can I do this? How to organize the data well and how to

I've got a list of 5 matrices that are each 5 x 6. I'd like to end up with a 5 x 6 matrix that contains the mean value of the 5 original matrices. I can do this by brute force, but there must be a better way than making each matrix into a vector and then remaking a matrix thanks very much for any help david freedman ll=list(structure(c(9.7, 17.6, 20.8, 24.1, 33.8, 14.5, 25.7, 29.8,

Hi, I am very new to R and I've been trying to work through the R book to gain a better idea of the code (which is also completely new to me). Initially I imputed my data from a text file and that seemed to work ok, but I'm trying to examine linear relationships between gdist and gair, gdist and gsub, m6dist and m6air, etc. This didn't work and I think it might have something to do

Reposting the data did not help. We do not like to guess, and doing so takes a great deal of time that is likely wasted. Rows are observations. Columns are variables. In Excel, the first row will be variable names and all subsequent rows will be observations. Income is the first variable. It has seven states: $10, $25, $40, $75, >$75, "No", "Answer" MF is the second