similar to: multiple domain and winbind use default domain

On Fri, 19 Aug 2016 09:22:50 +0200 BLINDAUER Emmanuel via samba <samba at lists.samba.org> wrote: > Hello > I'm preparing a new fileserver, based on jessie + sernet 4.2.10 > packages. the server is bound to a forest, "AD" where users account > are stored, and subdomains "PSI" for computers and some local accounts > The Active directory forest is

Having problems with rfc2307 user ids. This was working briefly and now it’s not. samba and winbind v 2.4.2.10+dfs wbinfo -u lists all the domain users wbinfo -g lists all the domain groups getent group lists all the local groups and the AD domain groups that have a UNIX gid set getent passwd lists only the local users, then pauses for a moment, then nothing. AD users can’t log in and can’t

Dear R users, I am new to R. I would like to find *maximum likelihood estimators for psi and alpha* based on the following *log likelihood function*, c is consumption data comprising 148 entries: fn<-function(c,psi,alpha) { s1<-sum(for(i in 1:n){(c[i]-(psi^(-1/alpha)*(lag(c[i],-1))))^2* (lag(c[i],-1)^((-2)*(alpha+1)) )}); s2<- sum(for(m in 1:n){log(lag(c[m],-1)^(((2)*alpha)+2))});

I'm trying to upgrade from samba3 -> 4. I ran this command: WORKDIR=/usr/local/mobius /usr/local/samba/bin/samba-tool domain classicupgrade --dbdir=$WORKDIR/var --use-xattrs=yes --realm=infinityhealthcare.com $WORKDIR/smb.conf but it failed with the error given in this email's subject. What does it mean, and how do I fix it? This is just another is a growing line of errors that

Hi all, I'm trying to fit a nonlinear regression by "nlrob": model3=nlrob(y~a1*x^a2,data=transient,psi=psi.bisquare, start=list(a1=0.02,a2=0.7),maxit=1000) However an error message keeps popping up saying that the function psi.bisquare doesn't exist. I also tried psi.huber, which is supposed to be the default for nlrob: model3=nlrob(y~a1*x^a2,data=transient,psi=psi.huber,

Dear R list, I have a function specifying my log-likelihood, and now I need to set the constraint that *alpha > kappa*, could anyone help me with setting this in my function? the function is defined as follows: mll <- function(param){ n <- length(x) psi <- numeric(n) psi[1] <- 1.0 a0 <- exp(param[1]); a1 <-exp(param[2]); b1 <- exp(param[3]); *alpha *<-

ClassicUpgrade of my samba3 data to samba4 fails, with this error: ERROR(<class 'passdb.error'>): uncaught exception - Unable to get id for sid Full log of the classicupgrade is at the end of this email. Project member on this list, Andrew Barlett, wrote that the issue is probably that my Samba 3 passdb was passable in an NT 4 DC mode, but is actually 'invalid' :

Hi there, I'm trying to solve a ML problem where the likelihood function is a function of two numerical procedures and I'm having some problems figuring out how to do this. The log-likelihood function is of the form L(c,psi) = 1/T sum [log (f(c, psi)) - log(g(c,psi))], where c is a 2xT matrix of data and psi is the parameter vector. f(c, psi) is the transition density which can be

I have a general question about coefficients estimation of the mixed model. I simulated a very basic model: Y|b=X*\beta+Z*b +\sigma^2* diag(ni); b follows N(0,\psi) #i.e. bivariate normal where b is the latent variable, Z and X are ni*2 design matrices, sigma is the error variance, Y are longitudinal data, i.e. there are ni

Hi all, To implement more profile-guided optimizations, we’d like to use ProfileSummaryInfo (PSI) and BlockFrequencyInfo (BFI) from more passes of various types, under the new pass manager. The following is what we came up with. Would appreciate feedback. Thanks. Issue It’s not obvious (to me) how to best do this, given that we cannot request an outer-scope analysis result from an inner-scope

Overall seems fine to me. On 3/11/19 8:12 PM, Hiroshi Yamauchi wrote: > Here's a revised approach based on the discussion: > > - Cache PSI right after the profile summary in the IR is written in > the pass pipeline. This would avoid the need to insert > RequireAnalysisPass for PSI before each non-module pass that needs it. > PSI can be technically invalidated but unlikely

I got some R code that I don't understand. Question as comment in code //where is t comming from, what is phi inverse rAC <- function(name, n, d, theta){ #generic function for Archimedean copula simulation illegalpar <- switch(name, clayton = (theta < 0), gumbel = (theta < 1), frank = (theta < 0), BB9 = ((theta[1] < 1) | (theta[2] < 0)), GIG = ((theta[2] < 0) |

On 3/14/19 2:04 AM, Hiroshi Yamauchi wrote: > > > On Wed, Mar 13, 2019 at 2:37 PM Fedor Sergeev <fedor.sergeev at azul.com > <mailto:fedor.sergeev at azul.com>> wrote: > >> >> - Add a new proxy ModuleAnalysisManagerLoopProxy for a loop pass >> to be able to get to the ModuleAnalysisManager in one step and >> PSI through it. >

Dear All, could someone please shed some light on the use of the .C or .Fortran function: I am trying load and running on R the following function // psi.cpp -- psi function for real arguments. // Algorithms and coefficient values from "Computation of Special // Functions", Zhang and Jin, John Wiley and Sons, 1996. // // (C) 2003, C. Bond. All rights reserved. // //

Hi all, following is my R -code and shows the error given below > n <- 100 > k<-2 > x1 <-c(1, 3);x2 <- c(2,5) > X <- matrix(c(0,0), nrow = 2, ncol = n) > for(i in 1:k) + X[i, ] <- mh1.epidemic(n,x1[i],x2[i]) Error in X[i, ] <- mh1.epidemic(n,x1[i],x2[i]):   number of items to replace is not a multiple of replacement length   > psi <-t(apply(X, c(1,2),

Hi R users, Is is possible for me to use the try function with boot? I would to do the bootstraping with a nonlinear model(it works well when R < 1000). But it does not work very well (when R is large) thus I try to use "try" to resolve. I put the try function in two cases: case1: put the try in front of the boot > c1.try<-try(boot(c1data, statistic = c1.fun,

On 3/4/19 10:49 PM, Hiroshi Yamauchi wrote: > > > On Mon, Mar 4, 2019 at 10:55 AM Hiroshi Yamauchi <yamauchi at google.com > <mailto:yamauchi at google.com>> wrote: > > > > On Sat, Mar 2, 2019 at 12:58 AM Fedor Sergeev > <fedor.sergeev at azul.com <mailto:fedor.sergeev at azul.com>> wrote: > > > > On 3/2/19 2:38 AM,

On Sat, Mar 2, 2019 at 12:58 AM Fedor Sergeev <fedor.sergeev at azul.com> wrote: > > > On 3/2/19 2:38 AM, Hiroshi Yamauchi wrote: > > Here's a sketch of the proposed approach for just one pass (but imagine > more) > > https://reviews.llvm.org/D58845 > > On Fri, Mar 1, 2019 at 12:54 PM Fedor Sergeev via llvm-dev < > llvm-dev at lists.llvm.org>

hi guys and gals ... How are you all ... i have to do something in robust regression by R programm , and i have some problems as following: *the first :* suppose w(r) =1/(1 r^2) and r <- c(7.01,2.07,7.061,5.607,8.502,54.909,12.222) and i want to exclude some values from r so that (abs(r)>4.9 )... after ,i want to used (w) to get on coefficients beta0 and beta1 (B1 <-

I try to code the ULS factor analysis descrbied in ftp://ftp.spss.com/pub/spss/statistics/spss/algorithms/ factor.pdf # see PP5-6 factanal.fit.uls <- function(cmat, factors, start=NULL, lower = 0.005, control = NULL, ...) { FAfn <- function(Psi, S, q) { Sstar <- S - diag(Psi) E <- eigen(Sstar, symmetric = TRUE, only.values = TRUE) e <- E$values[-(1:q)] e <-