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...? Thanks a lot for your help. Maomao ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ > p<-optim(c(0,0,0), f, method ="BFGS", hessian =T, y=y,X=X,W=W) There were 31 warnings (use warnings() to see them) > warnings() Warning messages: 1: In log(det(I_N - pd * wd - po * wo - pw * ww)) : NaNs produced 2: In log(det(I_N - pd * wd - po * wo - pw * ww)) : NaNs produced 3: In log(det(I_N - pd * wd - po * wo - pw * ww)) : NaNs produced 4: In log(det(I_N - pd * wd - po * wo - pw * ww)) : NaNs produced 5: In log(det(I_N - pd * wd - po * wo - pw * ww))...

...--- Signif. codes: 0 ?***? 0.001 ?**? 0.01 ?*? 0.05 ?.? 0.1 ? ? 1 1 observation deleted due to missingness ####################### a=3 b=4 c=5 A=1:a B=1:b C=1:c n=3 X=matrix(nr=a*b*c*n,nc=n) colnames(X)=LETTERS[1:n] for(i_a in 1:a-1) { for(i_b in 1:b-1) { for(i_c in 1:c-1) { for(i_n in 1:n-1) { X[((i_a * b + i_b) * c + i_c) * n + i_n + 1, ] = c(i_a+1, i_b+1, i_c+1) } } } } set.seed(0) Y=matrix(nr=a*b*c*n,nc=1) for(i in 1:(a*b*c)) { for(i_n in 1:n-1) { fa=X[i,'A'] fb=X[i,'B'] fc=X[i,'C'] #Y[(i-1)*n+i_n,1]= fa +fb +...

Hallo! I have the following function: cLL_beta <- function(beta){ sumterm=0 a=1 b=0 S=I_n-lambda*w R=I_n-rho*w det_R=det(S) det_S=det(R) for (i in 1:t){ b=i*n y_ausgew=y_tilde[a:b]#y_ausgew ist numeric y_aus=matrix(y_ausgew)#Typen anpassen X_ausgew=X[a:b,]#X_ausgew ist eine Matrix x_tilde=X_ausgew-1/t*x_t #x_tilde ist auch eine Matrix ####X_aus=matrix(X_ausgew) V1=R%*%(S%*%y_aus-x_til...

...er ########################## library(MASS) getQ<-function(object,t.index,i.index){ t.ind<-object[,t.index] i.ind<-object[,i.index] nam<-unique(i.ind) tim<-unique(t.ind) n<-nrow(object) N<-length(nam) T<-length(tim) I<-matrix(0,n,n) I[row(I)==col(I)] <- 1 I_N<-matrix(0,N,N) I_N[row(I_N)==col(I_N)] <- 1 I_T<-matrix(0,T,T) I_T[row(I_T)==col(I_T)] <- 1 D1<-data.frame() for(t in tim){ D1<-rbind(D1,I_N) } D1<-data.matrix(D1[as.vector(table(i.ind,t.ind))==1,]) D2<-data.frame() for(i in nam){ D2<-rbind(D2,I_T) } D2&l...

...int value 'i' is computed by a lot of int variables that are converted from ptr (p1,p2...pn) by ptrtoint, then if we inttoptr i to a point p, how should I decide which pointer value the 'p' forms? If those p_j are ptrtoint to a i_j, and the computation for i is i = i_0 + i_1 + ... i_n, does it mean we can take either p_j as a base pointer, and other int variables its offset, say we take p_2 as the base pointer, and the p from i points to p_2 + (i_0 + i_1 + i_3 + .. i_n) ? So in the transformation example, the result is different when we take %196 or %193 as a base po...

Hi R users, I am using the optim funciton to maximize a log likelihood function. My code is as follows: p<-optim(c(-0.2392925,0.4653128,-0.8332286, 0.0657, -0.0031, -0.00245, 3.366, 0.5885, -0.00008, 0.0786,-0.00292,-0.00081, 3.266, -0.3632, -0.000049, 0.1856, 0.00394, -0.00193, -0.889, 0.5379, -0.000063, 0.213, 0.00338, -0.00026, -0.8912, -0.3023, -0.000056), f,

...s computed by a lot of int variables that > are converted from ptr (p1,p2...pn) by ptrtoint, then if we inttoptr i > to a point p, how should I decide which pointer value the 'p' forms? > > If those p_j are ptrtoint to a i_j, and the computation for i is i = > i_0 + i_1 + ... i_n, does it mean >  we can take either p_j as a base pointer, and other int variables > its offset, say we take p_2 as the base pointer, and the p from i > points to >       p_2 + (i_0 + i_1 + i_3 + .. i_n) >  ? > > So in the transformation example, the result is different when we...

...s computed by a lot of int variables that > are converted from ptr (p1,p2...pn) by ptrtoint, then if we inttoptr i > to a point p, how should I decide which pointer value the 'p' forms? > > If those p_j are ptrtoint to a i_j, and the computation for i is i = > i_0 + i_1 + ... i_n, does it mean > we can take either p_j as a base pointer, and other int variables > its offset, say we take p_2 as the base pointer, and the p from i > points to > p_2 + (i_0 + i_1 + i_3 + .. i_n) > ? So, in your example, if you do: i1 = ptrtoint p1; i2 = ptrtoint p2;...

...of int variables that >> are converted from ptr (p1,p2...pn) by ptrtoint, then if we inttoptr i >> to a point p, how should I decide which pointer value the 'p' forms? >> >> If those p_j are ptrtoint to a i_j, and the computation for i is i = >> i_0 + i_1 + ... i_n, does it mean >>  we can take either p_j as a base pointer, and other int variables >> its offset, say we take p_2 as the base pointer, and the p from i >> points to >>       p_2 + (i_0 + i_1 + i_3 + .. i_n) >>  ? >> >> So in the transformation example, the...

...xpressions used as GEP indices. I assume, GEP indices (except indexing into struct) are interpreted as signed integers. It isn't explicitly stated in the LangRef, but the code seems to treat them this way. Am I correct? If the result of an affine expression: a_1*i_1 + a_2*i_2 + ... + a_n*i_n is interpreted as signed value during the program run, it should be safe to assume during the program analysis that all operations (coefficients) are signed - signed evaluation of such an expression will bring the same result as evaluation of the expression using original signedness and interpr...

...t >>> are converted from ptr (p1,p2...pn) by ptrtoint, then if we inttoptr i >>> to a point p, how should I decide which pointer value the 'p' forms? >>> >>> If those p_j are ptrtoint to a i_j, and the computation for i is i = >>> i_0 + i_1 + ... i_n, does it mean >>>  we can take either p_j as a base pointer, and other int variables >>> its offset, say we take p_2 as the base pointer, and the p from i >>> points to >>>       p_2 + (i_0 + i_1 + i_3 + .. i_n) >>>  ? >>> >>> So in the...

On Mon, Apr 4, 2011 at 7:10 AM, John Criswell <criswell at illinois.edu> wrote: > On 4/4/2011 6:45 PM, Eli Friedman wrote: >> >> On Mon, Apr 4, 2011 at 5:02 PM, Arushi Aggarwal<arushi987 at gmail.com> >>  wrote: >>> >>>> Hi, >>>> Is it correct to convert, >>>>   %196 = load i32* %195, align 8                

...re converted from ptr (p1,p2...pn) by ptrtoint, then if we inttoptr i >>>> to a point p, how should I decide which pointer value the 'p' forms? >>>> >>>> If those p_j are ptrtoint to a i_j, and the computation for i is i = >>>> i_0 + i_1 + ... i_n, does it mean >>>>  we can take either p_j as a base pointer, and other int variables >>>> its offset, say we take p_2 as the base pointer, and the p from i >>>> points to >>>>       p_2 + (i_0 + i_1 + i_3 + .. i_n) >>>>  ? >>>&gt...

On 4/4/2011 6:45 PM, Eli Friedman wrote: > On Mon, Apr 4, 2011 at 5:02 PM, Arushi Aggarwal<arushi987 at gmail.com> wrote: >> >>> Hi, >>> Is it correct to convert, >>> %196 = load i32* %195, align 8 ;<i32> [#uses=1] >>> %197 = zext i32 %196 to i64 ;<i64> [#uses=1] >>> %198 =

>However, there is one issue I have ignored - possibility of overflow in >the index expression. Suppose, we have such a loop: > for (i8 i = 0; i != 200; ++i) { > A[2 * i + 5] = ... > ... = A[2 * i + 3] > } >If both index expressions are evaluated in 8-bit arithmetic, >then the dependence equation should be solved in modular arithmetic: > 2 * i + 5 == 2 * (i +

...g independence of random vectors. It satisfies 0<=R<=1 and R=0 only if independence holds. Distance covariance V determines a statistically consistent test of independence. The distance covariance test is theoretically related to, but different from the original test based on coefficient I_n implemented in indep.etest. The new dcov.test is faster by a factor O(n) than indep.etest. With the introduction of a second and faster test, we provide a new function indep.test with a choice of methods to obtain either test. The original indep.etest is now deprecated. Reprints of the article...

...g independence of random vectors. It satisfies 0<=R<=1 and R=0 only if independence holds. Distance covariance V determines a statistically consistent test of independence. The distance covariance test is theoretically related to, but different from the original test based on coefficient I_n implemented in indep.etest. The new dcov.test is faster by a factor O(n) than indep.etest. With the introduction of a second and faster test, we provide a new function indep.test with a choice of methods to obtain either test. The original indep.etest is now deprecated. Reprints of the article...

Dear all, I'm looking for a function that calls the inverse F-distribution. Something equivalent to FINV in matlab or excel. Does anyone know if such a function already exists for R? (I haven't been able to find one.) Thanks for any leads. Best, Jennifer

...D@std@@V?$allocator at D@2@@std@@@Z) libbackend.lib(dbfactory_remote.obj) : error LNK2001: ????????? "public: virtual class Xapian::Document::Internal * __thiscall RemoteDatabase::open_document(unsigned int,bool)const " (?open_document at RemoteDatabase@@UBEPAVInternal at Document@Xapian@@I_N at Z) libnet.lib(progclient.obj) : error LNK2001: ????????? "public: virtual class Xapian::Document::Internal * __thiscall RemoteDatabase::open_document(unsigned int,bool)const " (?open_document at RemoteDatabase@@UBEPAVInternal at Document@Xapian@@I_N at Z) libnet.lib(tcpclient.obj) : er...