similar to: meaning of glm(value ~ .,

Hi. I started with a file which was a sparse 982x923 matrix and where the last column was a variable to be predicted. I did principle component analysis on it and arrived at a new 982x923 matrix. Then I ran the code below to get a neural network using nnet and then wanted to get a confusion matrix or at least know how accurate the neural net was. I used the first 22 principle components only for

Hi. I have an object. I think it is a list. > str(corTFandPCA) num [1:922, 1:5] -0.0226 -0.0504 -0.0208 -0.0582 -0.0257 ... - attr(*, "dimnames")=List of 2 ..$ : chr [1:922] "abdomen.2" "abdomimal.3" "abdominal.4" "aberration.5" ... ..$ : chr [1:5] "PC1" "PC2" "PC3" "PC4" ... I want to order it

Hi team I had installed OCFS2 on RHEL5.0 . every thing looks fine but when I was installing CRS on the node I got error message OCFS2 is not supported. Can you please put some light on this. Please find other info below [root at eregtest1 client]# uname -a Linux eregtest1.admin.abdn.ac.uk 2.6.18-92.el5 #1 SMP Tue Apr 29 13:16:15 EDT 2008 x86_64 x86_64 x86_64 GNU/Linux i am using RHEL 5.0

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Folks, I'm trying to wrap my head around something that happened in our environment. Basically, we noticed the error in /var/log/messages with no other errors. "Mar 16 13:38:02 dbo3 kernel: (3712,3):o2hb_do_disk_heartbeat:963 ERROR: Device "sdb1": another node is heartbeating in our slot!" Usually there are a

I''m no good at SQL and I have a question that will hopefully be fairly easy to answer. I''m using acts_as_paranoid which instead of deleting a record adds a deleted_at column with the datetime the row was deleted. I want to have a find_by_sql filter out any row where deleted_at is not null. I have (at least the relevant parts): #a couple working filters here. filters <<

# I am sure that I could be more efficient than this but how? Thanks in advance. #GPS in Decimal Degrees in the form longitude latitude RM215 <- matrix(c(-82.1461363, 33.5959109), nrow=1) SC <- matrix(c(-82.025888, 33.606454), nrow=1) RM202 <- matrix(c(-81.9906723, 33.5027653), nrow=1) RM198 <- matrix(c(-81.926823, 33.4634678), nrow=1) HC <- matrix(c(-81.920505, 33.46192), nrow=1)

Do so by simply re-using _show_registers(). Signed-off-by: Jan Beulich <jbeulich@suse.com> --- a/xen/arch/x86/x86_64/traps.c +++ b/xen/arch/x86/x86_64/traps.c @@ -225,6 +225,7 @@ void double_fault(void); void do_double_fault(struct cpu_user_regs *regs) { unsigned int cpu; + unsigned long crs[8]; watchdog_disable(); @@ -235,22 +236,18 @@ void do_double_fault(struct

Hola a todos Esta es mi primera pregunta en el grupo, y es sencilla pero me tiene atascado. Estoy tratando de cortar mi mapa de (poner limites en UTM) en un lugar definido como mi area de estudio (en este caso el sur de chile). Pero creo no estar usando bien la función CRS ponendo bien los limites requeridos. > study_area <- readRDS("CHL_adm0.rds") > study_area_UTM <-

Hi all, I'm faced with a problem applying the sp package: The projection argument in readShapePoly(Shapefile,proj4string="CRS class argument") e.g.: CRS("+proj=aea +lat_1=46 +lat_2=73 +lat_0=60 +lon_0=84 +x_0=0 +y_0=0 +ellps=clrk66 +units=m +no_defs") doesn't have any impact on the plotted object. I also tested the simple example: xy = cbind(x = 2 * runif(100) -

Hi, I am using in my workflow gIntersection from sp package. Part of my relevant sessionInfo is: R version 4.0.3 (2020-10-10) Platform: x86_64-w64-mingw32/x64 (64-bit) Running under: Windows 10 x64 (build 17763) attached base packages: [1] stats graphics grDevices utils datasets methods base other attached packages: [1] CircStats_0.2-6 boot_1.3-25 MASS_7.3-53 stringr_1.4.0

Dear all, I am trying to project my LongLat-maps to a plane. The ultimate purpose is to do a search of points in vicinity of other points using overlay-commands (sp) with radius in km. I am applying spTransform (package rgdal) and it gives my some curious results. An example. Let's take a point lying somewhere in Germany, zone=32U x <- 8.968735 y <- 49.454735 After conversion I

Dear all, I have been trying to convert coordinates from longitude/latitude to utm but I got an error. As soon as the longitude coordinate is greater than 90, I get the folloowing error message: "error in pj_transform: latitude or longitude exceeded limits" Here is what I did: SP<-SpatialPoints(cbind(126.59,-14.30),proj4string=CRS("+proj=longlat"))

summary: I can display a lon-lat map on a lattice::layerplot, and I can display a Lambert conformal conic (LCC) map on a spam::image, but I can't display an LCC map on a lattice::layerplot. Example follows. What am I doing wrong? details: I've been using `lattice` (via `rasterVis`) successfully to display global atmospheric data, which works well enough (though I am definitely intrigued

Hi, I am trying to do a lasso regression using the lars package with the following data (see attached): FastestTime WinPercentage PlacePercentage ShowPercentage BreakAverage FinishAverage Time7Average Time3Average Finish 116.90 0.14 0.14 0.29 4.43 3.29 117.56 117.77 5.00 116.23 0.29 0.43 0.14 6.14 2.14 116.84 116.80 2.00 116.41 0.00 0.14 0.29 5.71 3.71 117.24

Hello everyone, I want to get a 1km by lkm grid raster image using my csv data. If I call latitude=a, longitude=b and preciptation=c. a<-(1,2,3,4,5) b<-(6,7,8,9,10) c<-(10,20, 30,40, 50) Then I found an example in r help which goes like pts = read.table("file.csv",......) library(sp) library(rgdal) proj4string(pts)=CRS("+init=epsg:4326") # set it to lat-long pts =

Dear R People: I'm sure that this is a very simple problem, but I have been wresting with it for some time. I have the following file that has the following one line: CRS("+init=epsg:28992") Fair enough. I scan it into R and get the following: > u [1] "CRS(\"+init=epsg:28992\")" > gsub(pattern='\"',replacement='"',x=u) [1]

Hi, I'm trying to use transform my mercator locations into utm but I'm doing something wrong because only x is transformed ... see > xy.sp SpatialPoints: loni lati [1,] -8.85 38.16 [2,] -9.19 37.99 [3,] -9.11 37.97 [4,] -9.06 38.15 [5,] -9.03 37.87 [6,] -9.14 37.81 [7,] -9.09 37.70 [8,] -8.95 37.45 [9,] -9.17 37.37 [10,] -9.00 37.34 Coordinate Reference

Hi ALL, Can you please help me on how to determine the prediction error for ordinary kriging?Below are all the commands i used to generate the OK plot: rsa2 <- readShapeSpatial("residentialsa", CRS("+proj=tmerc +lat_0=39.66666666666666 +lon_0=-8.131906111111112 +k=1 +x_0=0 +y_0=0 +ellps=intl +units=m +no_defs")) x2 <- readShapeSpatial("ptna2",

Salutations, Long story short: I need to create an SPDF to superimpose on a Google map. I have .shp file which has a long list of locations listed in (what I guess must be) UTM. I need to transform these into lon, lat. My use of spTransform, however, keeps giving me the wrong results. For what it's worth, it only seems to be messing up the latitude. My final line of code looks like this:

I have searched your FAQ''s and read the documentation on your site as well as googling. I am not able to figure this out. If you have any ideas can you please help. I am using the linux-ha failover with redundant firewalls. As part of the function of the linux-ha software consists a service called heartbeat which is a connection from each failover node through a serial cable or ethernet.