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...fy the above relation.... Hmm... Somewhat related, I would also like to plot a line in 3 d space... Finally, if you are feeling really brave, I am interested in doing all of this based on sums generating vectors (I know there is a linear algebra term for this) -- ie generate the plane based on c_1*v_1 + c_2*v_2 for c_1 and c_2 in reals. Thanks again to all you helpful folks! W

Dear All, I would like to generate m positive real numbers c_i, I=1,...,m, such that (1) c_1 + c_2 + ... + c_m=m, (1) after being ordered into c_1 >= c_2 >= .... >=c_m>0, we have that c_m is of the same order of m^(-1/8), when m is sufficiently large. Thanks, -Chee [[alternative HTML version deleted]]

...ssume that all bits of the ‘|undef|‘ could be 0, and optimize the ‘|and|‘ to 0. Likewise, it is safe to assume that all the bits of the ‘|undef|‘ operand to the ‘|or|‘ could be set, allowing the ‘|or|‘ to be folded to -1." As a result, LHS = (undef & undef) | (undef & undef) = c_1 | c_2 where c_1 and c_2 are constants and as a result, And finally, LHS = c where c is a constant; not undef. Please correct me if I am missing something. Best Regards, soham On 9/13/2016 7:27 PM, Sanjoy Das wrote: > Hi Soham, > > Soham Chakraborty wrote: > > As a result,...

Dear all, It seems to be a recurrent problem to me and I am asking your help to get over it once for all ... My idea is : I have variables C_1, C_2, C_3 ... that corresponds to vectors of size n, and I would like to cbind them. I get a vector of their names using : temp<- ls(pat="C") And I like to find a way to use this vector temp as an argument to cbind. Unfortunately, my various trials failed, here are some sampl...

...j} * phi_{ij}; (1 - mu_{ij}) * phi_{ij}) y_{ij} = mu_{ij} + w_{ij} * *with* *logit(mu_{ij}) = Beta_{0i} + Beta_{1i} * x1_{ij} + b2 * x2_{ij} log(phi_{ij}) = Gamma_{0i} + Gamma_{1i} * z1_{ij} + c2 * z2_{ij} * *Beta_{0i} = b_0 + u_{0i} Beta_{1i} = b_1 + u_{1i} Gamma_{0i} = c_0 + v_{0i} Gamma_{1i} = c_1 + v_{1i} * *The vector* *(u_{0i}, u_{1i})'* *has normal distribution with mean* *(0, 0)'* *and covariance matrix* *sigma_{00} sigma_{01} sigma_{10} sigma_{11} * *The vector* *(v_{0i}, v_{1i})'* *has normal distribution with mean* *(0, 0)'* *and covariance matrix* *delta_{00} delta...

...* phi_{ij}; (1 - mu_{ij}) * phi_{ij}) y_{ij} = mu_{ij} + w_{ij} * *with* *logit(mu_{ij}) = Beta_{0i} + Beta_{1i} * x1_{ij} + b_2 * x2_{ij} log(phi_{ij}) = Gamma_{0i} + Gamma_{1i} * z1_{ij} + c_2 * z2_{ij} * *Beta_{0i} = b_0 + u_{0i} Beta_{1i} = b_1 + u_{1i} Gamma_{0i} = c_0 + v_{0i} Gamma_{1i} = c_1 + v_{1i} * *The vector* *(u_{0i}, u_{1i})'* *has normal distribution with mean* *(0, 0)'* *and covariance matrix* *sigma_{00} sigma_{01} sigma_{10} sigma_{11} * *The vector* *(v_{0i}, v_{1i})'* *has normal distribution with mean* *(0, 0)'* *and covariance matrix* *delta_{00} delta...

...rs, I hope to divide the original dataset into several subsets and output these multilple datasets. But errors appeared in my loops. See example. ###### a<-c(1:10) b<-c(rep(1,3),rep(2,3),rep(3,4)) c<-data.frame(a,b) #c is the example data num<-c(unique(b)) # I hope to get the subsets c_1.csv,c_2.csv and c_3.csv #Errors for (i in num) { c_num<-c[c$b==num,] write.csv(c_num,file="c:/c_num.csv") } Warning messages: 1: In c$b == num : longer object length is not a multiple of shorter object length 2: In c$b == num : longer object length is not a multiple of shor...

...y quick and dirty solution to avoid being listed on our internal security problem's list. This patch is for dovecot 2.0.9 which is included in Redhat Enterprise Linux 6.2: *** src/login-common/ssl-proxy-openssl.c 2010-12-30 10:42:54.000000000 +0100 --- src/login-common/ssl-proxy-openssl.c_1 2012-03-20 09:48:28.359508087 +0100 *************** *** 924,930 **** X509_STORE *store; STACK_OF(X509_NAME) *xnames = NULL; ! SSL_CTX_set_options(ssl_ctx, SSL_OP_ALL | SSL_OP_NO_SSLv2); if (*set->ssl_ca != '\0') { /* set trusted CA cert...

...onal upon the variance parameters. The paper is fairly clear except that some important level of detail is missing. For instance, when we first meet Q_(i): / \ / \ | Z_i X_i y_i | | R_11(i) R_10(i) c_1(i) | | | = Q_(i) | | | Delta 0 0 | | 0 R_00(i) c_0(i) | \ / \ / the text indicates that the Q-R factorization is limited to the...

Thanks for your answers. Another example of unsound transformation on Boolean algebra. According to the LLVM documentation (http://llvm.org/docs/LangRef.html#undefined-values) it is unsafe to consider ' a & undef = undef ' and ' a | undef = undef ' but 'undef xor undef = undef' is safe. Now, given an expression ((a & (~b)) | ((~a) & b)) where a and b are

Hi, I have a data-matrix: > PID sato hrs fim health 214 3 4.376430 6.582958 5 193 6 4.361825 3.138525 6 8441 6 4.205771 3.835886 7 7525 6 4.284489 3.245139 6 6806 7 4.168926 2.821833 7 5682 7 1.788707 1.212653 7 5225 6 1.651463 1.436980 7 4845 6 1.692710 1.267359 4 4552 5 1.686448 1.220539 6

-----BEGIN PGP SIGNED MESSAGE----- Hash: SHA1 Hi *, I am new to this list, so please excuse me if this has been covered before (unfortunately the search function at http://www.ruby-forum.com/forum/10 is disabled at the moment). If yes, then a pointer to a solution would be great. I want to create a sortable tree with scriptaculous Sortable. There are several categories and subcatgories: cat_a

...al upon the variance parameters. The paper is fairly clear except that some important level of detail is missing. For instance, when we first meet Q_(i): / \ / \ | Z_i X_i y_i | | R_11(i) R_10(i) c_1(i) | | | = Q_(i) | | | Delta 0 0 | | 0 R_00(i) c_0(i) | \ / \ / the text indicates that the Q-R factorization is limited to the...

Dear Users, Consider a multivariate time series model: a_1*y(t)-...-a_k*y(t-k)=b+[c_1*z(t)-...-c_j*z(t-j)] i.e., a simple multivariate time series model with one exogenous variable. I would like to know what package can I use to do the following, using R: 1) Select k and j jointly; 2) Estimate the model; 2) Forecast h=4 steps ahead the estimated model; 4) Bootstrap the forecast, s...