similar to: Subset returning unexpected result

Dear R Users, I have a data frame of 4 columns and ~58000 rows, the top of which looks like this: > head(max_out) Latitude Longitude Model Obs 1 -0.25 -49.25 4 4 2 -0.25 -50.25 4 5 3 -0.25 -50.75 4 4 4 -0.25 -51.25 3 11 5 -0.25 -51.75 6 4 6 -0.25 -52.25 12 5 The above shows, for each coordinate point, the

Dear all, I am encountering some issues with my data and need some help. I am trying to run glm analysis with a presence/absence variable as response variable and several explanatory variable (time, location, presence/absence data, abundance data). First I tried to use the glm() function, however I was having 2 warnings concerning glm.fit () : # 1: glm.fit: algorithm did not converge # 2:

Dear R users, A have a dataframe (matrix) with two collumns (plot, and diameter (d)). I want all diameters values for different combination of plots. For example I want all d values for all posible combination, 100C2 (all d values for plot 1 with all d values in the plot 2.......with all d values from plot 1 with all d values from plot 100, ...... with all d values from plot 99 with all d values

Dear all, I want to improve my adj - R sq. I 've chequed some established models and they introduce two times the same variable, one transformed, and the other not. It also improves my adj - R sq. But, isn't this bad for the collinearity? Do I interpret coefficients as usual? Estimate Std. Error t value Pr(>|t|) (Intercept) 1.73140 7.22477 0.240

Hi All, as a CCNA student and wishing to eventualy do CCSP, I wanted to learn all about what hackers use/do to infiltrate networks, and was introduced to dsniff at a Linux meeting, TLUG, in Tokyo, but, am having problems installing it. Please see below. checking for Berkeley DB with 1.85 compatibility... /usr/local/BerkeleyDB.4.4 configure: error: db_185.h or libdb.a not found in

Hi, I noticed some time ago that, for instance, named vectors that are really makes str() really slow when displaying the names attribute. I don't know exactly when this started, but it wasn't the case say 1-2 years ago. Example (on a WinXP 1.8GHz): > s <- 1:1000; names(s) <- s > system.time(str(s)) Named int [1:1000] 1 2 3 4 5 6 7 8 9 10 ... - attr(*, "names")=

Hi, Since update to 2.6.37 I can''t build openwrt on my btrfs buildroot anymore. I''m not sure if this is related to the other flush-btrfs-1 thread. plenty of diskspace is free: /dev/mapper/cruor-build 97G 68G 27G 73% /opt/build It always hangs when openwrt builds the ext4 image and runs tune2fs on it.

Dear all, As I am new to the R community - although eager to advance- I would like to pose a question to the community. I have an SPSS file which I have imported it in R (with the read.spss command) which conists of scale (continuous) variable "adiponectin" and the corresponding categorical value "death" (0=No, 1=Yes). In all there are 60 observations (among which

Dear all, I am attempting to perform what should be a relatively simple calculation on a number of data frame columns. I am hoping to find the average on a per-row basis for each of the 50 columns. If on a particular row a 'NA' value is encountered, then this should be ignored and the mean formed on the basis of the other rows. However, I'm finding that the end result for each row

Hello, Using the dataset below I produce a soil.texture plot (R code for this included at the end). One will notice I have plotted the points based on whether or not they are in a region called 'upstream' or 'downstream'. I'm curious if there is a way to somehow extract counts of the number of points (red points and blue points) falling within each classification (e.g. silty

Hello, Just wondering why I am unable to run this in parallel. A dput of my dataset is attached at the end. Please use to create my data object. I want to run this function in parallel (not sure if this is an efficient implementation): #Function to calculate the time to maturity for the option require(fCalendar,quietly=TRUE) #Trying to calculate the trading days

I've attached the latest version of my autovectorization patch. Working through the test suite has proved to be a productive experience ;) -- And almost all of the bugs that it revealed have now been fixed. There are still two programs that don't compile with vectorization turned on, and I'm working on those now, but in case anyone feels like playing with vectorization, this patch

On Tue, 2011-11-08 at 12:12 +0100, Tobias Grosser wrote: > On 11/08/2011 11:45 AM, Hal Finkel wrote: > > I've attached the latest version of my autovectorization patch. > > > > Working through the test suite has proved to be a productive > > experience ;) -- And almost all of the bugs that it revealed have now > > been fixed. There are still two programs that

Dear R users, I want to aggregate all *d *data from all combination of n *plots* taken by k. Thank very much! My data is like that: plot d 1 14 1 13 1 12 1 14 1 18 1 20 1 21 1 43 1 108 1 43 2 41 2 61 2 83 2 61 2 84 2 45 2 21 2 12 2 11 ... 100 10 100 12 -- --- Catalin-Constantin ROIBU Forestry engineer, PhD Forestry Faculty of Suceava

On 11/08/2011 11:45 AM, Hal Finkel wrote: > I've attached the latest version of my autovectorization patch. > > Working through the test suite has proved to be a productive > experience ;) -- And almost all of the bugs that it revealed have now > been fixed. There are still two programs that don't compile with > vectorization turned on, and I'm working on those now,

On 11/08/2011 03:36 PM, Hal Finkel wrote: > On Tue, 2011-11-08 at 12:12 +0100, Tobias Grosser wrote: >> On 11/08/2011 11:45 AM, Hal Finkel wrote: >>> I've attached the latest version of my autovectorization patch. >>> >>> Working through the test suite has proved to be a productive >>> experience ;) -- And almost all of the bugs that it revealed

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Dear all, I am unable to understand how Hline() works in tabular(). I've read the vignette and the help page, and here this example compiles perfectly fine: latex( tabular( Species + Hline() + 1 ~ Heading()*mean*All(iris), data=iris) ) However, if I try it on my own data it fails. Consider this: set.seed(1) Xa <- data.frame(p=rep(c("First group","Second

Hello R users, For the last few days I am struggling with the following task: my data.frame: A1 A2 A3 B1 B2 B3 58.81 53.292 54.501 13.013 17.39 19.407 56.02 56.251 54.033 20.099 13.15 10.411 55.376 53.099 57.625 13.396 21.031 13.22 58.584 53.194 54.218 13.038 16.854 19.289 55.7 55.921 53.847 19.942 13.153 9.828 55.093 52.934

Hello, I'm cc'ing R-Help. Sorry but your question was asked 3.5 years ago, I really don't remember it. Can you please post a question to R-Help, with a reproducible example that describes your problem? Rui Barradas ? Citando catalin roibu <catalinroibu at gmail.com>: > Dear Rui, > ? > I helped me some time ago with a code..... regarding aggregated data >