search for: dummy1

Dear all, I would like to ask one question related to statistics, for specifically on defining dummy variables. As of now, I have come across 3 different kind of dummy variables (assuming I am working with Seasonal dummy, and number of season is 4): > dummy1 <- diag(4) > for(i in 1:3) dummy1 <- rbind(dummy1, diag(4)) > dummy1 <- dummy1[,-4] > > dummy2 <- dummy1 > dummy2[dummy2 == 0] = -1/(4-1) > > dummy3 <- dummy1 - 1/4 > > head(dummy1) [,1] [,2] [,3] [1,] 1 0 0 [2,] 0 1 0 [3,] 0 0...

...profile, subsequent calls to dyn.load() issued at the R prompt result in loss of symbol names in the other dll (although not until one tries re-dyn.load()ing the second dll; re-dyn.load()ing just one of them works OK). This has occurred only since installing R 2.1.0. Example: Contents of file dummy1.c: --------------------------- #include <R.h> #include <Rdefines.h> SEXP dummy1() { Rprintf("this is dummy1() in C\n") ; return R_NilValue ; } --------------------------- Contents of file dummy2.c ------------------------- #include <R.h> #include <Rdefines....

Hello, Is there a better way to use paste such as: a = paste(colnames(list.indep)[1],colnames(list.indep)[2],colnames(list.indep)[3],colnames(list.indep)[4],colnames(list.indep)[5],sep="+") > a [1] "aa+dummy1+dummy2+bb+cc" I tried a = paste(colnames(list.indep)[1:5],sep="+") > a [1] "aa" "dummy1" "dummy2" "bb" "cc" But it will not give me the way I want. Thanks, Rebecca ---------...

Dear list members, is it possible to set some options only inside a function so that the original options are restored once the function is finished or aborted due to an error? Until now I do something like: dummy=function() { old.options=options(error=dummy1()) .... options(old.options) } This works for most cases but when the function terminates because of an error and its last command is not run, error=dummy1() still remains as an option. Is there any way around this? Cheers Jannis

...n _one_ host and i have tried that mentioned "clever juggling of network devices" on my system, but i didn`t succedd. some coraid employee recommended trying linux-bridging - so i created two dummy interfaces (module dummy.ko), created a bridge "aoe-bridge" and added dummy0 and dummy1 to that bridge. then i "connected" AoE-driver to dummy0 and vblade server process to dummy1 and would have expected that this should work. unfortunately, it failed to work and from what it seems it wasn`t a problem with AoE or vblade but with the bridge, because i couldn`t see (tcpdump)...

Hello R-users I was puzzled by some strange results of an analysis and I found out what is for me a strange behaviour (I won't dare to say a bug) in both plot and points (and I suspect lines and other kind of lower level plots). If you try the following code: > data<-data.frame(dummy1=c(1:10),dummy2=c(1:10)) > plot(data$dummy1,data$dummy3) A plot of the values of dummy1 against an index is produced, even when dummy3 does not exist. Same happens with points. Also, the index is used as the x-axis, so specially when using points in a plot already made, the results can be mis...

Hello, I have a data frame > mdl.summary est.coef std.err t.stat intercept 0.0011625517 0.0002671437 4.351784 aa -0.0813727439 0.0163727943 -4.969997 dummy1 -0.0002534873 0.0001204000 -2.105376 dummy2 -0.0007784864 0.0001437537 -5.415417 bb -0.0002856727 0.0001090387 -2.619920 cc 0.0003563825 0.0001114803 3.196820 and would like to store it to a pdf file, I use p...

...ux system with 4 ethernet interfaces, eth0 goes to the internet, eth1, eth2, and eth3 are NAT''d LANs. I want to use an ingress filter to prioritize bandwidth (downstream from internet) to various IPs. I want to sett it up something like this.... eth0 <--[NAT]--> dummy0 <---> dummy1 <---> eth1,eth2,eth3 dummy1 should have an ingress filter on it controling outbound bandwidth to the internet dummy0 should have an ingress filter on it controling inbound bandwidth from the internet Let''s say... eth0 is 10.53.62.2/30 dummy0 is 192.168.255.1/24 dummy1 is 192.168.2...

...0x100 lc <- as.integer(100); cov.matrix <- matrix(runif(lc * lc), nrow=lc) cov.matrix <- t(cov.matrix) %*% cov.matrix ## the usual way of getting the Cholesky decomposition c0 <- chol(cov.matrix) ## direct call of the Fortran routine; the code is ## taken from the R-code of `chol' dummy1 <- .Fortran("chol", cov.matrix, lc, lc, v = matrix(0, nr = lc, nc = lc), info = integer(1), DUP = FALSE, PACKAGE = "base") c1 <- dummy1$v ## The third way. ## The code seems working very well... but? dummy2 <- double(lc * lc) .Fortran(&quo...

...iginal variables, as well as insert some code into the original source code. just like: ============= original source code ============= int a[10]; void fun1 () { // some source code here } ========================================= ============= instrumented source code ============= int dummy1[20]; int a[10]; int dummy2[30]; void fun1 () { // instrumented source code 1 // some source code here // instrumented source code 2 } ============= instrumented source code ============= Apparently, dummy1 and dummy2 may cause pressure of data cache, and instrumented source code 1 a...

...f later in the "error:" label you keep the "if (ret)" condition. > for (i = 0; i < nr_qgroups; ++i) { > char *line = lines[i + 2]; > struct guestfs_int_btrfsqgroup *this = > &ret->guestfs_int_btrfsqgroup_list_val[i]; > - uint64_t dummy1, dummy2; > - char *p; > > - if (sscanf (line, "%" SCNu64 "/%" SCNu64 " %" SCNu64 " %" SCNu64, > - &dummy1, &dummy2, &this->btrfsqgroup_rfer, > - &this->btrfsqgroup_excl) != 4) { > +...

tl;dr - a renamed dummy interface is not persisting across reboots on Cent6. I have a situation where I need to rename a dummy interface on my system. I have a total of 3 dummy interfaces: dummy0 dummy1 adummy0 I've been doing some puppet testing in a vbox VM to get this all sorted out to deploy to a group of boxes. Every time I reboot my VM, it comes up WITHOUT adummy0, but I notice there is now an unconfigured dummy2. I've tried everything from adding aliases to /etc/modprobe.d/dummyo...

As Pino's comment, we should take advantage of macro CLEANUP_FREE_STRING_LIST v4: remove some redundant strdup v3: fix test case failure v2: properly initialize lines Chen Hanxiao (3): do_btrfs_qgroup_show: fix a bad return value do_btrfs_subvolume_list: fix a bad return value btrfs: use CLEANUP_FREE_STRING_LIST for list free daemon/btrfs.c | 70

When I callculate a linear model, then I can compute via confint the confidencial intervals. the interval level can be chosen. as result, I get the parameter of the model according to the interval level. On the other hand, I can compute the prediction-values for my model as well with predict(object, type=c("response") etc.). Here I have also the possibility to chose a level for the

...ULL) { reply_with_perror ("malloc"); - goto error; + free (ret); + return NULL; } for (i = 0; i < nr_qgroups; ++i) { char *line = lines[i + 2]; struct guestfs_int_btrfsqgroup *this = &ret->guestfs_int_btrfsqgroup_list_val[i]; - uint64_t dummy1, dummy2; - char *p; - if (sscanf (line, "%" SCNu64 "/%" SCNu64 " %" SCNu64 " %" SCNu64, - &dummy1, &dummy2, &this->btrfsqgroup_rfer, - &this->btrfsqgroup_excl) != 4) { + if (sscanf (line, "%m...

...64 @@ -1298,7 +1298,7 @@ do_btrfs_qgroup_show (const char *path) for (i = 0; i < nr_qgroups; ++i) { char *line = lines[i + 2]; - struct guestfs_int_btrfsqgroup *this = + struct guestfs_int_btrfsqgroup *this = &ret->guestfs_int_btrfsqgroup_list_val[i]; uint64_t dummy1, dummy2; char *p; -- 2.1.0

...custom) Here is /etc/xen/scripts/network-custom: # !/bin/bash # network-custom script=/etc/xen/scripts/network-bridge case $1 in start) $script start vifnum=0 bridge=xenbr0 netdev=eth0 $script start vifnum=1 bridge=xenbr1 netdev=dummy0 $script start vifnum=2 bridge=xenbr2 netdev=dummy1 ;; stop) $script stop vifnum=0 bridge=xenbr0 netdev=eth0 $script stop vifnum=1 bridge=xenbr1 netdev=dummy0 $script stop vifnum=2 bridge=xenbr2 netdev=dummy1 ;; status) $script status ;; *) echo 'Unknown command: ' $1 echo 'Valid commands are: start...

Hello, I am looking for a function which allows to calculate the confidence interval for a standard mortality ratio. I do have vectors with the number of observed and expected death. Has anybody a hint where to look? Best, Stefan

...source code. just like: > > ============= original source code ============= > > int a[10]; > > void fun1 () { > // some source code here > } > > ========================================= > > ============= instrumented source code ============= > > int dummy1[20]; > int a[10]; > int dummy2[30]; > > void fun1 () { > // instrumented source code 1 > // some source code here > // instrumented source code 2 > } > > ============= instrumented source code ============= > > Apparently, dummy1 and dummy2 may cause...

...ng firm in the second with the same #year, industry and dimension (the dimension doesn't need to be exactly the #same, it could vary in an interval of +/- 10%, for example) #My reproducible example firm1<-sort(rep(1:10,5),decreasing=F) year1<-rep(2000:2004,10) industry1<-rep(20,50) dummy1<-c(0,0,1,1,0,0,1,1,0,1,1,1,0,0,0,0,0,0,1,1,1,1,0,0,0,0,0,0,0,0,1,0,1,0,1,1,1,1,1,0,0,1,0,0,0,0,0,1,1,1) dimension1<-c(2120,345,2341,5678,10900,4890,2789,3412,9500,8765,4532,6593,12900,123,2345,3178,2678,6666,647,23789, 2189,4289,8543,637,23456,781,35489,2345,5754,8976,3245,1234,25,1200,2345,2...