similar to: Draw text with a box surround in plot.

R2.7.1, WinXP Hi, I have a polygon inside a circle as follows: radius <- 3 x <- seq(-radius,radius,length=2000) y <- sqrt(radius^2-x^2) xx <- c(x,-x) yy <- c(y,-y) plot(xx,yy, xlim=c(-radius,radius),ylim=c(-radius,radius), type="l", ylab="", xlab="", axes=F) radius <- 2.7 x1 <- seq(-radius,radius,length=2000) y1 <- sqrt(radius^2-x1^2)

RNG in R and Splus 3.4 Prof. Ripley asked the details of the example. We were doing parametric bootstrap, so it is similar to simulation. Anyway here is the details. We start with a sample of 19 positive numbers. We know the sample is from truncated exp(0.3)...only the truncation point, theta, is unknown. In other words, the sample can be generated from something like x1 <- rexp(100,

RNG in R and Splus 3.4 Prof. Ripley asked the details of the example. We were doing parametric bootstrap, so it is similar to simulation. Anyway here is the details. We start with a sample of 19 positive numbers. We know the sample is from truncated exp(0.3)...only the truncation point, theta, is unknown. In other words, the sample can be generated from something like x1 <- rexp(100,

For a given random variable rv, for instance, rv = rnorm(1000), I plot its density curve and calculate some quantiles: plot(density(rv)) P10P50P90 = = quantile(rv,probs = c(10,50,90)/100) I would like to color the area between P10 and P90 and under the curve and mark the P50 on the curve. > rv = rnorm(1000) > plot(density(rv)) > P10P50P90 = = quantile(rv,probs = c(10,50,90)/100) Could

I wish to rearrange the matrix, df, such that all there are not repeated x values. Particularly, for each value of x that is reated, the corresponded y value should fall under the appropriate column. For example, the x value 3 appears 4 times under the different columns of y, i.e. y1,y2,y3,y4. The output should be such that for the lone value of 3 selected for x, the corresponding row entries

Hi R-experts, suppose I have a list with containing data frame elements: [[1]] (Intercept) y1 y2 y3 y4 -6.64 0.761 0.383 0.775 0.163 [[2]] (Intercept) y2 y3 -3.858 0.854 0.834 Now I want to put them into ONE dataframe like this: (Intercept) y1

Hello all! I want to estimate parameters in a MIMIC model. I have one latent variable (ksi), four reflexive indicators (y1, y2, y3 and y4) and four formative indicators (x1, x2, x3, x4). Is there a way to do it in R? I know there is the SEM library, but it seems not to be possible to specify formative indicators, that is, observed exogenous variables which causes the latent variable. Thanks,

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 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

I would like to generate pseudo-random numbers between two numbers using R, up to a given distribution, for instance, rnorm. That is something like rnorm(HowMany,Min,Max,mean,sd) over rnorm(HowMany,mean,sd). I am wondering if dnorm(runif(HowMany, Min, Max), mean, sd) is good. Any idea? Thanks. -james

Hi all, I'm extracting the name of the term in a regression model that dropterm specifies as the least significant one, and I'm assigning this name to an object. However, when I use update(), it ignores this object. Is there a way I can make it not ignore it? A reproducible example is below: > lm(x1~1+y1*y2+y3+y4,data=anscombe)->my.lm >

Hello again, First I want to thank all the people who answered my question about line width in graphs. I promise I will learn the 'par' help page by heart for the end of the month ! I now want to trace some ellipses to emphasize groups of data. I found how to trace circles with 'symbols()', but no ellipse. I'm planning on writing my own function based on

I would like to sum/mean/min a list of lists and numbers to return the related lists. -1+2*c(1,1,0)+2+c(-1,10,-1) returns c(2,13,0) but sum(1,2*c(1,1,0),2,c(-1,10,-1)) returns 15 not a list. Using the suggestions of Gabor Grothendieck, Reduce('+',list(-1,2*c(1,1,0),2,c(-1,10,-1))) returns what we want, c(2,13,0). However, it seems that this way does not work to mean/min. So, how to

I am wondering if you know how to return by function or show in boxplot, the indexes of unusual points, such as, points that are outside the box or in [Q3+1.5IQR,Max]. For example, > boxplot(c(4,rnorm(20),8)) There are 2 unusual points 4 and 8. How to show the indexes of 4 and 8 in the boxplot or return them by function? Thanks, -james

Hi   I have four groups   y1=c(1.214,1.180,1.199) y2=c(1.614,1.710,1.867,1.479) y3=c(1.361,1.270,1.375,1.299) y4=c(1.459,1.335) Is there a function that can give me the length for each, like the made up example below?   >function(length(y1:y2) [1] 3 4 4 2 [[alternative HTML version deleted]]

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, I would like to create a plot of y1,y2,y3,y4 against x for several subjects such that y1 and y2 are plotted against x in one panel and y3 and y4 against x in another panel. Thus if there are 3 subjects I should end up with 6 panels. Is there a simple way of doing so (i.e. without calling xyplot() several times, and then padding the results together)?? Regards S?ren

I would like to conduct an extra sum-of -squares test that compares a full MANOVA model (with all 1st order interactions) to a reduced model (no interactions) to determine if I can drop all interactions at the same time. This is analagous to an extra sum-of-squares F-test in ANOVA, but instead using MANOVA. Is there a command in R that does this? If not, is there a command that calculates

Dear All, I need some help arranging data that was imported. The imported data frame looks something like this (the actual file is huge, so this is example data) DF: IDKey X1 Y1 X2 Y2 X3 Y3 X4 Y4 Name1 21 15 25 10 Name2 15 18 35 24 27 45 Name3 17 21 30 22 15 40 32 55 I would like to create a new data frame with the following NewDF: IDKey X Y Name1 21 15 Name1

Hello, If I have two correlation matrices (e.g. one for each of two treatments) and then perform cor() on those two correlation matrices is this third correlation matrix interpreted as the correlation between the two treatments? In my sample below I would interpret that the treatments are 0.28 correlated. Is this correct? > var1<- c(.000000000008, .09, .1234, .5670008, .00110011002200,