similar to: glm() function not finding the maximum

Hello, I am trying to filter a data set like below so that the peaks in the Phase value are more obvious and can be identified by a peak finding function following the useful advise of Carl Witthoft. I have written the following for(i in length(data$Phase)){ newphase=if(abs(data$Phase[i+1]-data$Phase[i])>6){ data$Phase[i+1] }else{data$Phase[i] } } I get the following error which I have not

I need a little piece of advice concerning passing data frames into the functions. As I do a lot of similar fits at a time, I'd like to write a small function doing the fits for all relevant variables automatically. However, I usually get error messages of the following kind: (I present here a part of a test code). ##################################################### # Data set:

We have a Linux file server for a set of computer science and engineering labs where each lab contains machines running Mac OS X, Ubuntu Linux, or some incarnation of Windows. At times the these machines become almost unusable and I think I have narrowed the problem to smbd processes soaking up all the CPU on the server. Running 'top' on the server reveals a dozen or so entries like

I have sort of an emergency question for the list. One of my professors for an S-Plus intensive class distributed a function to produce partial regression plots. I need to run it under R, because I'm doing the homework on my home computer with a modem; hence I don't have the speed required to emulate X-Windows and run S Plus off one of the campus servers. Bottom line: I'm using R.

On 2016-05-25 19:13, Kelly Lesperance wrote: > Hdparm didn?t get far: > > [root at r1k1 ~] # hdparm -tT /dev/sda > > /dev/sda: > Timing cached reads: Alarm clock > [root at r1k1 ~] # Hi Kelly, Try running 'iostat -xdmc 1'. Look for a single drive that has substantially greater await than ~10msec. If all the drives except one are taking 6-8msec, but one is very

Dear R-list, I'm not sure what I've found about a function in DAAG package is a bug. When I was using cv.lm(DAAG) , I found there might be something wrong with it. The problem is that we can't use it to deal with a linear model with more than one predictor variable. But the usage documentation hasn't informed us about this. The code illustrates my discovery: > library(DAAG)

Hello, Thank you to all those great folks that have helped me in the past (especially Dennis Murphy). I have a new challenge. I often generate time-series data sets that look like the one below, with a variable ("Phase") which has a series of flat-topped peaks (sample data below with 5 "peaks"). I would like to calculate the phase value for each peak. It would be great to

Hi folks, The following are initial virtio-scsi + target vhost benchmark results using multiple target LUNs per vhost and multiple virtio PCI adapters to scale the total number of virtio-scsi LUNs into a single KVM guest. The test setup is currently using 4x SCSI LUNs per vhost WWPN, with 8x virtio PCI adapters for a total of 32x 500MB ramdisk LUNs into a single guest, along with each backend

Hi folks, The following are initial virtio-scsi + target vhost benchmark results using multiple target LUNs per vhost and multiple virtio PCI adapters to scale the total number of virtio-scsi LUNs into a single KVM guest. The test setup is currently using 4x SCSI LUNs per vhost WWPN, with 8x virtio PCI adapters for a total of 32x 500MB ramdisk LUNs into a single guest, along with each backend