similar to: Generating artificial datasets with a specific correlation coefficient.

I am running R 2.01 on Mac OS 10.3.7. Whenever I save graphs, they are saved as PDF files. Are there any other file formats to which I could save my graphs. I would like to directly export my graphs to MS Word, if possible. Thank you in advance. Sincerely, Jim Milks Graduate Student Environmental Sciences Ph.D. Program Wright State University 3640 Colonel Glenn Hwy Dayton, OH 45435

I am attempting to fit a logistic regression plane to a 3-D scatterplot (which was generated using scatterplot3d). I've noticed that the help pages of scatterplot3d include a function titled "plane3d." However, when I attempt to use the function, I get the following message: Error: couldn't find function "plane3d" I've searched the archives and found no

I have data on number of vines per tree for ~550 trees. Over half of the trees did not have any vines and the data is fairly skewed (median = 0, mean = 1.158, 3rd qu. = 1.000). I am attempting to investigate whether plot location (four sites), species (I'm using only the four most common species), or tree dbh has a significant influence on the number of vines per tree. When I

I have a data frame with two columns, one of which is a factor (Species) and the other is numeric (BA, which stands for basal area). Here's a sample: Species BA ACSA 55.7632696 FRAM 122.9933524 ACSA 67.54424205 ACSA 89.22123136 ACSA 82.46680716 ACSA 22.46238747 ACSA 19.94911335 ACSA 20.42035225 ACSA 19.00663555 ACSA 21.67698931 ACSA 57.80530483 ACSA 30.31636911 Dead 43.98229715 Dead

Dear All, I have a rather unusual problem. I have a set of data for a class in subsurface processes. From that dataset, I must calculate the slope of the best-fit line (which is the parameter of interest). The problem I have is twofold: 1) for the purposes of the exercise, I must force my best-fit line to go through the origin (0,0), and 2) the line must be linear, even though the data is

R gurus, I have a data set that looks something like this: Site Species DBH #Vines G PLOC 45.9 4 G ACNE 23.3 1 G ACNE 12.0 0 G FRAM 35.9 5 G AEGL 11.2 2 N PLOC 77.3 12 N JUNI 78.6 7 N ACNE 18.9 1 N ACNE 15.7 3 N ACRU 35.5 4 H ACSA2 24.1 6 H ULAM 35.2 7 There are 730 individual trees (22 species) from four sites in the actual data set. I would like to create a second data frame that

R gurus, I'm working on data analysis for a small project. My response variable is total vines per tree (median = 0, mean = 1.65, min = 0, max = 24). My predictors are two categorical variables (four sites and four species) and one continuous (tree diameter at breast height (DBH)). The main question I'm attempting to answer is whether or not the species identity of a tree has

I wish to generate a vector of uniformly distributed data with a defined correlation to another vector The only function I have been able to find doing something similar is corgen from the library ecodist. The following code generates data with the desired correlation to the vector x but the resulting vector y is normal and not uniform distributed library(ecodist) x <- runif(10^5) y

Dear R Gurus, Let's get the technical details out of the way first: Computer: 1.83 GHz MacBook R version 2.5.1 I have a data set that contains the following variables: site, species, total.vines. I need to partition the main data set by site, the further select only those species that occurred at each site. When I select by site (site.name<-subset(data frame,Site=="Site

Hi!! I am trying to generate data with specific correlation using corgen method from the ecodist package. It does not seem to generate the data properly. I am listing the code below. Secondly, when I put the code given below all in one file and source it, it is unable to complete the task. But when I execute it one at a time it is able to complete it. Can someone point out any mistake that I may

Dear all: I have a regression model that has collinearity problems (between three regressor variables). I need a F-test that will allow me to compare between full (with all variables) and partial models (minus 1=< variables). The general F-test formula I'm using is: F = {[SS(full model) - SS(reduced model)] / (#variables taken out)} / MSS(full model) Unfortunately, the ANOVA table

Dear R experts, I am trying to simulate correlated binary data and have stumbled upon the following problem: With the help of "binarySimCLF" or "mvpBinaryEp" I have been able to simulate correlating binary vectors given certain mean values and a desired correlation. My problem is that these procedures do not allow you to specify the exact vector for which you want to generate

Hi everyone. Based on a dependent variable (y), I'm trying to generate some independent variables with a specified correlation. For this there's no problems. However, I would like that have all my "regressors" to be orthogonal (i.e. no correlation among them. For example, y = x1 + x2 + x3 where the correlation between y x1 = 0.7, x2 = 0.4 and x3 = 0.8. However, x1, x2 and x3

Hi, how can I produce random data which lies around a straight line with angle 45 degree. Similar to this image: http://zoonek2.free.fr/UNIX/48_R/g134.png Cheers -- View this message in context: http://old.nabble.com/Random-data-tp26513822p26513822.html Sent from the R help mailing list archive at Nabble.com.

I would like to perform partial mantel tests on only within group values, with "between group" values assigned to NA. This is possible in package ncf partial.mantel.test, however this sues a different permutation to that used in ecodist.ecodist will not accept data with NA values, returning a "matrix is not square error. is it possible to perform this test in ecodist? many thanks

The title says it all. Does anyone know of a way to save your packages when you upgrade to a new version of R? This may seem petty, but I'm accumulating enough packages that having to download and install each of them anew every time I install a new version of R is rather of a pain. Ideally, I would like the new version of R to recognize the packages I've installed on the

I am using the function metaMDS with jaccard distances to ordinate a set of constituent by site matrix. I can post this data if it would be helpful, but it is large to include in an email. I can also provide reproducable code if necessary. I would like to get an R^2 value for the axes of the ordination configuration that I get with metaMDS in the vegan package is there a way to do this- is it

I would like to put confidence intervals on a mantel corellogram they are already calculated in the pmgram object but I am unsure how I get the x value in order to plot them? package(ecodist) X<-1:100 Y<-rnorm(1:100) Z<-rnorm(1:100) XY<-dist(data.frame(X,Y)) YX<-dist(data.frame(Y,X)) my.mgram<-mgram(XY,XZ) plot(my.mgram) print(my.mgram) > print(my.mgram) $mgram

Dear Dr.Goslee and anyone may intrested in matrix manipulate, I am using your ecodist to do mantel and partial mantel test, I have locality data and shape variation data, and the two distance matrixs are given as belowings. When I run the analysis, it is always report that the matrix is not square, but I didn't know what's wrong with my data. Would you please help me on this. I am quite

I have a table like this: Date TIME Q A a 1 A b 2 A c 3 B a 4 B b 5 B c 6 C a 7 C b 8 C c 9 I want use R language to turn it to a matrix like : a b c A 1 2 3 B 4 5 6 C 7 8 9 I am new to R , anyone can help? Thanks in advance! have a table like this: Date TIME Q A a 1 A b 2 A c 3 B a