search for: indictor

...least 2 reasons: 1) I need to modify the files after I import them by adding three new parameters to each file prior to combining them into a common data.frame For example one of my files is called SRF_DryDry_stats.dbf. The name of the file tells me that it refers to two conditions; 1) SRF = an indictor region field, and 2) DryDry = dry hydrological conditions. I also know that the data refer to a particular species. The data in the file include some general summarizing statistics (Min, Max, Range, Mean, and STD). After modifying the file, I need a species field, the SRF field and the hydro cond...

...m N(1,1) for these 10 data, since the indicator for the 20 data is randomized) . For example, the 10 data's indicator could be 0 0 0 1 0 1 1 0 0 0 (0 means the observation is from N(0,1) and 1 indicates the observations is from N(1,1)) B: still the same 20 data generate data above. I want the indictor is forced to be balanced in the first 10 data. That is, if I use the first 10 data, 5 are from N(0,1) and 5 are from (1,1). For example, the 10 data's indicator could be 0 1 1 0 0 1 0 1 1 0 How can I generate the 20 data . Sorry it is a little confusing. I want to generate the data not the in...

...t is no longer true and therefore I cannot use the Cox model. The code I used to get the MFP model was: coxfitf <- mfp(Surv(with.Withtime,with.Wcens)~fp(all.age),family=cox,data=nearma,select=0.05,verbose=TRUE) where with.Withtime is the time to treatment withdrawal, with.Wcens is the censoring indictor for the event and all.firstint is the age at baseline. To look at the competing risks regression modelling when age in untransformed, I can use the following code: fitn<-crr(nearma$with.Withtime,censaeb,as.matrix(nearma$all.age),failcode=2,cencode=0) where censaeb is the censoring indicator whi...

...d_layout + +\begin_layout Standard + +\change_inserted -385801441 1370345028 + +\family typewriter +summary_indicator +\family default + contains the guest address of a byte value to be used as a summary indicator + which is set to != 0 every time the host wants to signal the guest for + any of the indictors and unset by the guest to signify that it received + the notification. + +\family typewriter +isc +\family default + is the interruption subclass to be used for the adapter interrupt. + Note that an isc/summary indicator pair must match for any subsequent requests + to set up adapter interrupts ....

Hi, here's again my proposal for adapter (thin) interrupt support for virtio-ccw devices, originally posted at http://marc.info/?l=linux-virtualization&m=137060143904927&w=2 The document is unchanged, only rebased against current master. Cornelia Huck (1): virtio-ccw: Document adapter interrupts. virtio-spec.lyx | 147 +++++++++++++++++++++++++++++++++++++++++++++++++++++-- 1

Hi, here's again my proposal for adapter (thin) interrupt support for virtio-ccw devices, originally posted at http://marc.info/?l=linux-virtualization&m=137060143904927&w=2 The document is unchanged, only rebased against current master. Cornelia Huck (1): virtio-ccw: Document adapter interrupts. virtio-spec.lyx | 147 +++++++++++++++++++++++++++++++++++++++++++++++++++++-- 1

Hi, here's a proposal to support adapter (aka thin) interrupts for virtio-ccw. The basic idea is to make host->guest signalling on s390 more lightweight. Normal I/O interrupts have two parts: an interrupt that is made pending on any of the guest cpus, and status that is made pending on the subchannel. This means that we need two exits for every interrupt. With adapter interrupts, only

Hi, here's a proposal to support adapter (aka thin) interrupts for virtio-ccw. The basic idea is to make host->guest signalling on s390 more lightweight. Normal I/O interrupts have two parts: an interrupt that is made pending on any of the guest cpus, and status that is made pending on the subchannel. This means that we need two exits for every interrupt. With adapter interrupts, only

...that). It then treats ## all non-numeric variables as if they were factors, and summarizes ## each in a say that I find useful. In particular, for each factor, ## it provides a table of the most frequently occurring values (the ## top "numLevels" values are represented). As a diversity indictor, ## it calculates the Entropy and NormedEntropy values for each ## variable. Note not all of this is original. It combines my code ## and R code from base/summary.R summarizeFactors <- function(dat = NULL, numLevels = 10, alphaSort = TRUE, digits = max(3, getOption("digits") - 3)) {...