similar to: Error in as.vector(data) optim() / fkf()

Hi, I'm trying to estimate the parameters of a state space model of the following form measurement eq: z_t = a + b*y_t + eps_t transition eq y_t+h = (I -exp(-hL))theta + exp(-hL)y_t+ eta_{t+h}. The problem is that the distribution of the innovations of the transition equation depend on the previous value of the state variable. To be exact: y_t|y_{t-1} ~N(mu, Q_t) where Q is a diagonal

Dear all The following is a very basic and beginner's question on loops. Suppose you have data (say, 1000 cases) with two variables named "answer" (string) and "class" (numeric). The latter runs from 1 to 78 and categorizes the data. I need to create a file "answer_1.txt" for the cases with class==1, and so on, up to "answer_78.txt" I have been

Hi, Can anyone tell me how to construct a simple VAR(1) time series with two variables using the dse package? I would like to end up with two time series y_1t = \phi_11 y_1,t-1 + \phi_12 y_2,t-1 + e_1t y_2t = \phi_21 y_1,t-1 + \phi_22 y_2,t-1 + e_2t Best regards, Sam.

For some small sample sizes I would like to exemplify the combinatorics underlying certain nonparametric tests like Mann-Whitney-Wilcoxon, Kruskal-Wallis and Spearman's rank correlation. I have written a function all.perm which delivers all permutations of 1,2,...,n and which works reasonably well. This can be used to generate P(R=r) of Spearman's rank correlation:

Hi, I wanted to know if there existed an good implementation in R of the following classical subset Integers : $P_{n,m} = {k_1, \ldots, k_m \in \mathbb{N} : k_1 + \ldots + k_m = n }$ for any integers $m < n$. There is an obvious not optimal code which would be to run through $m$ sums and put a boolean condition to report if the integers respect these condition but it would take $m^n$

Assume that we collect below data : - subjects = 20 males + 20 females, every single individual is independence, and difference events = 1, 2, 3... n covariates = 4 blood types A, B, AB, O http://r.789695.n4.nabble.com/file/n4245397/CodeCogsEqn.jpeg ?m = hazards rates for male ?n = hazards rates for female Wm = Wn x ?, frailty for males, where ? is the edge ratio of male compare to female Wn =

The officially sanctioned way to put the expression "lambda_1 = x" in a title is something like this: title(substitute(lambda[1] == lamb, list(lamb = x))) but suppose I have two lambdas and would like something like "lambda_1 = x_1 , lambda_2 = x_2" to appear. What then? Undoubtedly I'm missing something blindingly obvious with lists, but having tried several

Hi all; I recently have been used 'maxLik' function for maximizing G2StNV178 function with gradient function gradlik; for receiving this goal, I write the following program; but I have been seen an error  in calling gradient  function; The maxLik function can't enter gradlik function (definition of gradient function); I guess my mistake is in line ******** ,that the vector  ‘h’ is

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

Dear R users this may be a simple question - but i would appreciate any thoughts does anyone know how you would get one lower and one upper confidence interval for a set of data that consists of proportions. i.e. taking a usual confidence interval for normal data would result in the lower confidence interval being negative - which is not possible given the data (which is constrained between

List members, Via searches I've seen similar discussion of this topic but have not seen resolution of the particular issue I am experiencing. If my search on this topic failed, I apologize for the redundancy. I am attempting to generate random covariance matrices but would like the corresponding correlations to be uniformly distributed between -1 and 1. The approach I have been using is:

Rainer M Krug writes: > Thorsten Wiegand used in his paper Wiegand T., and K. A. Moloney 2004. > Rings, circles and null-models for point pattern analysis in ecology. > Oikos 104: 209-229 a statistic he called O-Ring statistic which is > similar to Ripley's K, only that it uses rings instead of circles. > > http://www.oesa.ufz.de/towi/towi_programita.html#ring

Hi, If I set df=2 in my smooth.spline function, is that equivalent to running a linear regression through my data? It appears that df=# of data points gives the interpolating spline and that df = 2 gives the linear regression, but I just want to confirm this. Thank you, Steven

Hi, I would like to know whether there exist algorithms to compute the coefficients or, at least, the degree of the minimal polynomial of a square matrix A (over the field of complex numbers)? I don't know whether this would require symbolic computation. If not, has any of the algorithms been implemented in R? Thanks very much, Ravi. P.S. Just for the sake of completeness, a

Hello list. I'm trying to rebuild the 2.6.9.67.0.20.EL kernel, but it fails even without modifications. How did I try it? Created a (non-root) build environment (not a mock ) Installed the kernel.scr.rpm and did a rpmbuild -ba --target=`uname -m` kernel-2.6.spec 2> prep-err.log | tee prep-out.log The build failed at the end: Processing files: kernel-xenU-devel-2.6.9-67.0.20.EL Checking

Signed-off-by: Scott Seago <sseago at redhat.com> --- AUTHORS | 17 ++++++ README | 10 +++ conf/ovirt-agent | 12 ++++ conf/ovirt-db-omatic | 12 ++++ conf/ovirt-host-browser | 12 ++++