similar to: Plotting multiple figures

Dear members, I want to create 8 graphs and write it into one page using mfrow=c(4,2). How to make all graphs (including the titles, legends, line types) to be scale down (resized proportionally). As an illustration, below is the code: pdf("testmfrow.pdf") par(mfrow=c(4,2)) x<-seq(1:10) y1<-rnorm(10) y2<-rnorm(10,mean=2,sd=1) y3<-rnorm(10,mean=3,sd=1)

Hi Yves lavaan looks like a very nice package. From the tutorial introduction I see you create path diagrams for some of the models you describe. How did you do this? I don't see a function for this in the package. I know there is a path.diagram function in the sem package that uses dot to draw the diagram, but I've always found the layouts from dot somewhat strange for path diagrams

R 2.2 on windows XP I have a dataset with multiple columns. Some of the columns represent independent variables, some represent dependent variables. I would like to run the same analyses on a fixed set of independent variables, changing only the dependent variable, e.g. y1-y2=x1+x2+x3 y3-y4=x1+x2+x3 y5-y6=x1+x2+x3, etc. I know I can write a function to perform the analyses, however in order to

Dear all, I am quite new to R; facing certain problems: Say, I have a text file( named as "try"): Year C1 C2 C3 C4 C5 C6 Y1 3.5 13.8 9.5 6.8 0.4 24.2 Y2 3.8 13.9 9.9 7.6 0.7 12.8 Y3 4.5 14.5 14.2 9.2 0.6 14.5 Y4 5.9 16.2 24.6 12.7 0.2 24.3 Y5 7.2 20.4 40.6 18.2 0.8 28.2 Y6 5.9 18.6 37.4 14.5 0.3 36.9 Y7 8.0 16.1 88.6 24.1 0.1 34.6 Y8 13.6 21.1 56.3 19.0 0.7 33.3 I wish to import the

Dear colleagues, I wish to create a figure with 6 plots arranged vertically with no spacing between them as they all have a common x-axis. However, using the code below I'm unable to get the plot area the same size for each plot. The bottom plot with the x-axis label is smaller than the others, as is the top plot which has larger margins. How can I get the plot region the same size for

http://biomet.oxfordjournals.org/cgi/reprint/86/3/677 biometrika1999 http://biomet.oxfordjournals.org/cgi/reprint/94/4/1006 biometrika2000 Hi All: I just want to try some luck. I am currenly working on my project,one part of my project is to reanalysis the kenward cattle data by using the method in Mohsen's paper,but I found I really can get the same or close output as he did,so,any

Hi Dear all; I would like to create a plot for regression coefficients with each independent variable (x) along the side and the phenotypes (y) across the top (as given below). For each data point, direction and magnitude of effect could be color and significance could be the size of the circle? Is this possible? I would greatly be appreciated your help. Thanks, Greg y1 y2 y3 y4 y5 y6 x1

I am unfamiliar with R and I’m trying to do few statistical things like GLM and GAM with it. I hope my following questions will be clear enough: My datas ( y(i,j ))are run off triangles for example : J=1 J=2 J=3 I=1 1 2 3 I=2 4 5 I=3 6 My model is : E[y(i,j)] =m(i,j) Var[y(i,j)] =constant *m(i,j) Log(m(i,j)) = eta (i,j) eta (i,j) = c + alpha(i)

Dear list, I have problem that I cannot solve and would like to ask your opinion. I tried to ask a few days ago already but got no answer and all my attempts to solve it by myself since then failed. Sorry for repeated posting! Here the problem broken down a bit. My problem basically is, that I want to use the elements of a character vector as names for objects and by recalling only the

Fwiw, encoding magnitude in color is generally a bad idea. Using area(*not* radius) is also not great, but maybe it will work for you. See here for some explanation: https://www.amazon.com/Visual-Display-Quantitative-Information/dp/0961392142/ref=sr_1_1?s=books&ie=UTF8&qid=1518092778&sr=1-1&keywords=Tufte Bert On Feb 7, 2018 11:13 PM, "greg holly" <mak.hholly at

Hello everyone, I want to transform a data.frame into an array (lets call it mydata), where: mydata[[1]] is the first imputed dataset...and for each mydata[[d]], the first p columns are covariates X, and the last one is the outcome Y. Lets assume a simple data.frame: Imputed = data.frame( X1 = c(1,2,1,2,1,2,1,2, 1,2,1,2,1,2,1,2), X2 =

This is one of those instances where a less superficial knowledge of R's technical details comes in really handy. What you need to do is convert the data frame to a single (numeric) vector for, e.g. a matrix() call. This can be easily done by noting that a data frame is also a list and using do.call(): ## imp is the data frame: do.call(c,imp) X11 X12 X13 X14 X15 X16 X17 X18 X19

I am trying to do a surface profile plot. data is X                  Y(1)             Z(1) 1-jan-02       2002        number 2-jan-02       2002        number . . . 1-jan-03       2003 (Y2)     number Z(2) 2-jan-03       2003 (Y2)     number Z(2) . . . until dec 31 2007.   I used the plot3d funtions to build a scatter point plot. Call rinterface.rrun("library(rgl)") Call

Dear help-list members, I am a student at Durham University (UK) conducting a PhD on spatial representation in baboons. Currently, I'm analysing the effect of sampling interval on home range calculations. I have followed the baboons for 234 days in the field, each day is represented by about 1000 waypoints (x,y coordinates) recorded at irregular time intervals. Consecutive waypoints in

Hello everyone, Thank you for this. Nonetheless it is not exactly want i need. I need mydata[[1]] to provide the values for all 3 variables (Y, X1 and X2) of the first imputation only. As it stands it returns the whole database. Any ideas? Best, ioanna ________________________________ From: Bert Gunter <bgunter.4567 at gmail.com> Sent: 24 May 2018 16:04 To: Ioanna Ioannou Cc:

Dear R-users; Previously I posted a question about the problem of rank deficiency in summary.manova. As somebody suggested, I'm attaching a small part of the data set. #*************************************************** "test" <- structure(.Data = list(structure(.Data = c(rep(1,3),rep(2,18),rep(3,10)), levels = c("1", "2", "3"), class =

Hi After melt you can change levels of your factor variable. Again with the toy example. > levels(temp$variable) [1] "y1" "y2" "y3" "y4" > levels(temp$variable) <- levels(temp$variable)[c(2,4,1,3)] > levels(temp$variable) [1] "y2" "y4" "y1" "y3" > And you will get graphs with this new levels ordering.

Hi Petr; Thanks for your reply. It is much appreciated. A small example is given below for 4 independent and 4 dependent variables only. The values given are regression coefficients.I have looked ggplot documents before writing to you. Unfortunately, I could not figure out as my experience in ggplot is ignorable Regards. Greg y1 y2 y3 y4 x1 -0.19 0.40 -0.06 0.13 x2 0.45 -0.75 -8.67 -0.46 x3

Hi there, if I copy an x11() graphics device to an eps-file (with dev.copy2eps()) the font in the legend is very large and doesn't fit to the legend box in the eps-file (same with a postscript file). I'm not sure if this is a R problem rather than a ghostscript one. But is there a way to solve this problem in R or depends this on my ghostscript installation? System: R Version 1.2.3 on

Dear R developers, I noticed a bug in the stats4 package, specifically in the confint method applied to ?mle? objects. In particular, when some ?fixed? parameters define the log likelihood, these parameters are stored within the mle object but they are not used by the ?confint" method, which retrieves their value from the global environment (whenever they still exist). Sample code: >