similar to: R-help

Dear r-help, I am trying to plot several scatter plots with marginal histograms on one page. Ideally, a page is equally divided into 4 figure regions. Within each figure region, a scatter plot with marginal histograms will be plotted. I followed Dr. Paul Murrell's code released online to successfully plot the scatter plot with marginal histograms. The code applies "layout()" to

Hi all, I am running regressions with many covariates, most of which remain the same each time (control variables). Instead of writing 30 demographic variables every regression, is there a way I could call them all at once using a variable called, perhaps "demog"? I have tried: > demog <- list(age1, age2, age3) but I get an error when I try to call a list in a regression. I also

Hi, Bert: Yes, I studied the functions you suggested, but I didn't get to adapt it to my example whose reproducible code I sent in my first email. Here it is the code of the functions I studies: ## par par(mfrow = c(2, 3)) par(cex = 0.6) par(mar = c(3, 3, 0, 0), oma = c(1, 1, 1, 1)) for (i in 1:6) { plot(1, 1, type = "n") mtext(letters[i], side = 3, line = -1, adj = 0.1, cex =

I'm trying to recreate a graph similar to the last one found on this link: https://sites.ualberta.ca/~lkgray/uploads/7/3/6/2/7362679/6c_-_line_plots_with_error_bars.pdf The difference is that I want budbreak on the top, and the temperatures at the bottom. I tried to set par before each graph and include lines, with no avail. Thanks, Bert. Andre On Mon, Jun 19, 2017 at 7:41 PM, Bert Gunter

Dear friends, I have the following dataframe: YEAR <- c(1996 , 1997, 1998, 1999, 2000, 2001, 2002, 2003, 2004 ) T_MAR <- c(2.8, 6.5, 5.4,2.4, 4, 4.1, 3, 4.4, 4.5) T_APR <- c(5.7, 7.8, 7.7, 4.6, 4.7, 6.2,5.7, 5.9, 7) T_MAY <- c(7, 8.8, 10, 6, 5.5, 7.6, 8.5, 7.3, 10.2) BUD <- c(87, 98, 93, 85, 89, 91, 87, 92, 92) BUD_SE <- c(3.6, 2, 2.4, 4, 2.4, 2.4, 4, 2.4, 3) g1 <-

Hi, I wanted to plot 2 lines on a single graph. Each graph has one axis that can be common. The code that I'm using is: ------------------------------------------------------- par(mfrow=c(1, 1)) x1 <- c(2, 4, 6, 8, 10, 12) x2 <- c(10, 20, 30, 40, 50, 60) y1 <- c(10,12,15,22,34,21) y2 <- c(40, 130, 150, 145, 40, 30) par(las=1, mar=c(4, 4, 2, 4)) plot.new()

Dear all, I found the last example of this link ( https://sites.ualberta.ca/~lkgray/uploads/7/3/6/2/7362679/6c_-_line_plots_with_error_bars.pdf) very similar to the one I need to make for my paper, and I think I got what I wanted by applying some of the suggestions of this mail list. Here it is the code I devised (maybe there will be further improvements from the list): YEAR <- c(1996 ,

Hello, my question is if I have two axes in a graphics as I can put him a different color al axis and to the number of the scale. ? Thanks. Ruben

Fairly often I make multi-plot figures. I know that there are several fancy ways to do that in R. I simply make the individual plots and then put then together in LyX. When plots are stacked on top of each other, in my area the journals like them like this: 4-| -| | | 3-| -| | | 2-| -| | | 1-| -| | | --+--+--+--+-- --+--+--+--+-- 4-| -|

How do I plot using multiple(2) y-axes? I have two series that use the same x-data, but have very different scales. Appreciate any feedback, Per Bak

Hi You are quite close. With slight modification of your code: par(mfrow = c(2, 1)) par(cex = 0.6) par(mar = c(0, 0, 0, 0), oma = c(4, 4, 0.5, 0.5)) par(tcl = -0.25) par(mgp = c(2, 0.6, 0)) plot(BUD~YEAR, type="o", ann=F, axes=F, pch=19, ylim=c(60,100),data=g1) axis(4, las=2) mtext("Bud Break (Julian Day)", side=4, padj=4) arrows(g1$YEAR,g1$BUD, g1$YEAR,g1$BUD + g1$BUD_SE,

1. Did you study the functions (esp. ?layout) to which I referred you? 2. Show us your code! -- "to no avail" is meaningless! -- Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Mon, Jun 19, 2017 at 7:01 PM, Andr? Luis Neves

Can anyone explain this behavior? Essentially, I've created a short file to be read in via source() that gets some descriptive information on a series of variables in a data frame. For each variable, I do three things: print('last.hc.actors') quantile(last.hc.actors,probs=seq(0,1,0.1),na.rm=T) stem(last.hc.actors) where the variable name is (in this case) last.hc.actors. All that

Dear All, I am fairly new to R. I work mainly in SAS. Now, I know that SAS is approved by the FDA for submissions. My question is, does the FDA approve {R} for clinical trial submissions. Also has anyone ever tried to produce TFL's using R. I would like to know how difficult it to produce the TFL's in R as compared to SAS. I know that in SAS it is not difficult once you know

Dear all, I am trying to write figures directly to a file using the jpeg() function. this_ylab=expression(paste("P",sep="")~lambda) this_xlab=expression(rho) jpeg("file_name.jpeg",width=100,height=100,units="mm",res=300) plot(input_values,output_values,pch=16,cex=cex_pt,xlab="",frame.plot=T,ann=F,axes=F) axis(side=2)

Estimados amigos, Tengo el siguiente set de datos: caps <- datos[datos$NombreDepartamento=="LANUS", c("CAPS", "personas", "PersonasRCVG", "Con12Meses")] caps$prevalencia <- round(caps$PersonasRCVG/caps$personas*100,1) caps CAPS personas PersonasRCVG Con12Meses prevalencia 2345 2345 1347 132 211 9.8 2363

Hi, Could you help me? i have a problem with file on disperse volume. When i try to read this from mount point i recieve error, # md5sum /mnt/glfs/vmfs/slake-test-bck-m1-d1.qcow2 md5sum: /mnt/glfs/vmfs/slake-test-bck-m1-d1.qcow2: Input/output error Configuration and status of volume is: # gluster volume info vol1 Volume Name: vol1 Type: Disperse Volume ID:

See ?layout ?split.screen ?par (the mfrow and mfcol values) depending exactly on what you want to do and how you want to do it. Essentially, these all allow you to make separate plots at different regions of the device. Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in

Hi all, I'm running a multidimensional scaling model on data that are first transformed into a similarity matrix using the program daisy in the cluster package. If I already provide the similarity matrix, the plotting routine will give me the variable names on the plot itself. But, it seems that when I use the daisy program to create the similarity matrix, I can't get the program

Greetings, again. This is not strictly an R question, so please feel free to ignore it if you like. My question is about the substance of correspondence analysis. Specifically, is it appropriate to use ca on a matrix of values such that the columns and/or rows are not mutually exclusive? To be more detailed: - The standard use of ca is illustrated in the example of corresp() (from MASS):