similar to: How to account for autoregressive terms?

The device name prefix for IDE hard drives used to be `ad' but now is `ada' (http://www.freebsd.org/doc/handbook/disks-naming.html). For virtio hard drives it is `vtbd'. Under an MBR partition table a slice will be used, so the name of the first partitions will be either `ada0s1a' or `vtbd0s1a'. Under a GPT partition table, where no slice is needed, the name of the first

The device name prefix for IDE hard drives used to be `ad' but now is `ada' (http://www.freebsd.org/doc/handbook/disks-naming.html). For virtio hard drives it is `vtbd'. Under an mbr partition table a slice will be used, so the name of the first partitions will be either ada0s1a or vtbd0s1a. Under a GPT partition table, where no slice is needed, the name of the first partition will be

This change refactors guestfs___has_windows_systemroot to guestfs___get_windows_systemroot. The new function returns a dynamically allocated char * which must be freed. The new function is no less efficient than before, as it returns the result of guestfs___case_sensitive_path_silently, which is required anyway. The new code is slightly more efficient than before, as it re-uses the result of this

Hello! I'm puzzled by the following problem. It occurs while trying to predict responses in a test-dataset using a linear model fitted with regFit from the rMetrics "fRegression"-package. All goes well when I call "predict" using the training dataset. However, a call using the test-dataset retuns an error message - telling me that the latter dataset provides variables

Because of previous automated commits, such as changing 'guestfs___' -> 'guestfs_int_', several function calls no longer lined up with their parameters, and some lines were too long. The bulk of this commit was done using emacs batch mode and the technique described here: http://www.cslab.pepperdine.edu/warford/BatchIndentationEmacs.html The changes suggested by emacs were

Previously posted: https://www.redhat.com/archives/libguestfs/2015-December/msg00038.html Inspection now really succeeds on a small number of simple guests. To test it out: $ ./run guestfish -v -x -a /tmp/centos-6.img ><fs> run ><fs> debug sh "guestfs-inspection --verbose" Rich.

Result of earlier copy and paste. --- align/scan.c | 35 ++++++++++--------- cat/cat.c | 39 +++++++++++---------- cat/filesystems.c | 69 +++++++++++++++++++------------------- cat/log.c | 35 ++++++++++--------- cat/ls.c | 61 +++++++++++++++++---------------- df/main.c | 43 ++++++++++++------------ diff/diff.c | 67

x<-c(-1.873....,-0.121) # 23 numerics; x.arma12 <- armaFit(x ~ arma(1,2)) #estimates y[t]= -0.11465 - 0.23767 y[t-1] - 0.14230 e[t-1] -0.85770 e[t-2] + e[t]; # ? how to predict 46 steps ahead based on 23 data points? # the following doesn't work since n is in armaSim rather than armaFit; predict(x.arima12, n.ahead=46) # Thanks ---------------------------------

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"

Hi useRs, I'm experiencing something quite weird with glm() and weights, and maybe someone can explain what I'm doing wrong. I have a dataset where each row represents a single case, and I run glm(...,family="binomial") and get my coefficients. However, some of my cases have the exact same values for predictor variables, so I should be able to aggregate up my data frame and

Hello R community, I have a question about the logistic regression function. Specifically, when the predictor variable has not just 0's and 1's, but also fractional values (between zero and one). I get a warning when I use the "glm(formula = ... , family = binomial(link = "logit"))" which says: "In eval(expr, envir, enclos) : non-integer #successes in a binomial

Hello R users, I am new to R and am wondering if anyone can help me out with the following issue: I wrote a function to build ts models using different inputs, but when R displays the call for a model, I cannot tell which variables it is using because it shows the arguments instead of the real variables passed to the function. (e.g Call: lm(formula = dyn(dep ~ lag(dep, -1) + indep)) --->

An embedded and charset-unspecified text was scrubbed... Name: sparse-fs_ext3_super.patch URL: <http://listman.redhat.com/archives/ext3-users/attachments/20050620/af49961a/attachment.ksh>

Hard to help without a short example dataset (please read posting guide!) posted with dput(). You likely want to "paste" together a title for your graph. see ?paste Rambler1 wrote > > Another simple question that is driving me crazy: > I have a for loop that loops through a matrix and pulls data from two > different variables, computes differences and runs a regression

I am using R on a Windows XP professional platform. The following code is part of a bigger one CODE press=function(y,x){ library(qpcR) models.press=numeric(0) cat("\n") dep=y print(dep) indep=log(x) print(indep) yfit=dep-PRESS(lm(dep~indep))[[2]] cat("\n yfit\n") print(yfit) yfit.orig=yfit presid=y-yfit.orig press=sum(presid^2)

In a function, say foo.glm for glm objects I want to use the name of the object as a label for some output, but *only* if a glm object was passed as an argument, not a call to glm() producing that object. How can I distinguish these two cases? For example, I can use the following to get the name of the argument: foo.glm <- function(object) { oname <- as.character(sys.call())[2]

Hello, Semi-new r user here and still learning the ropes. I am creating dummy variables for a dataset on stock prices in r. One dummy variable is called prev1 and is: prev1 <- ifelse(ret1 >= .5, 1, 0) where ret1 is the previous day's return. The variable "prev1" is created fine and works in my regression model and for running conditional statistics. However, when I call the

Could anyone tell me what am I doing wrong? > pro<-function(indep,dep){ + d<-data.frame(indep) + form<-formula(lm(dep~.,data=d)) + forward<-step(lm(dep~X1,data=d),scope=form,trace=0,direction='f') + return(forward) + } > pro(m,q) Error in inherits(x, "data.frame") : Object "d" not found Where q is a vector with the dependent variable's

Hi, How does the requirement that phi instructions have one value per predecessor basic block interact with indirectbr instructions? For instance, take the following code: L1: br i1 %somevalue, label %L2, label %L3 L2: %ret1 = i8* blockaddress(@myfunction, %L5) br label %L4 L3: %ret2 = i8* blockaddress(@myfunction, %L6) br label %L4 L4: %ret = phi i8* [%ret1, L2], [%ret2, L3]

libguestfs has used double and triple underscores in identifiers. These aren't valid for global names in C++. (http://stackoverflow.com/a/228797) These large but completely mechanical patches change the illegal identifiers to legal ones. Rich.