similar to: User-specified correlation structure (e.g., 2-banded Toeplitz)

Dear All: I am trying to fit a special case of a 2-banded Toeplitz correlation structure. A 2-banded Toeplitz has ones on the diagonal, a correlation, RHO1, on the first off-diagonal, and a correlation, RHO2, on the second off-diagonal, with zeros on all subsequent off-diagonals. After reading relevant sections in Mixed-Effects Models in S and S-PLUS (Pinheiro & Bates, 2000) and searching

Dear All: I am trying to fit a special case of a 2-banded Toeplitz correlation structure. A 2-banded Toeplitz has ones on the diagonal, a correlation, RHO1, on the first off-diagonal, and a correlation, RHO2, on the second off-diagonal, with zeros on all subsequent off-diagonals. After reading relevant sections in Mixed-Effects Models in S and S-PLUS (Pinheiro & Bates, 2000) and searching

Hi R users, I have a couple of questions about some problems that I am facing with regard to numerical integration and optimization of likelihood functions. Let me provide a little background information: I am trying to do maximum likelihood estimation of an econometric model that I have developed recently. I estimate the parameters of the model using the monthly US unemployment rate series

Hi, I'm trying to write a simple function like case1 <- function (m, cov, Q, R) { theta <- (acos(R/sqrt(Q^3))) beta <- (-2)*sqrt(Q)*cos(theta/3)+m[1]/3 rho1 <- (-2)*sqrt(Q)*cos((theta+2*pi)/3)+m[1]/3 rho2 <- (-2)*sqrt(Q)*cos((theta-2*pi)/3)+m[1]/3 stderrb <- deltamethod( ~(-2)*sqrt(Q)*cos(theta/3)+x1/3,m,cov) stderrr1 <- deltamethod(

I am looking for examples of code that demonstrates the fine tuning of the strip panels in lattice graphics and uses plotmath characters. The code for the graphic is as follows: xyplot(lagy ~ n | rho1 * rho2, data= data, layout=c(2,6), span = 1, xlab = "Sample Size", ylab = "Bias in the Coefficient for the Lag of X", type = "o") rho1 is a four level factor

hHllo, I'm looking for an algroithm to transform an existing toeplitz matrix (autocorrelation matrix) to the nearest positive semidefinite toeplitz matrix. I merely found an algorithm to transform an correlation matrix via the function nearcor() based on the algorithm of Higham. But as I examined, it destroys the toeplitz structure of my underlying matrix. Does any function already exist

Is there a function in r that let's you efficiently invert a positive definite symmetric Block Toeplitz matrix? My matrices are the covariance matrices of observations of a multivariate time series and can be 1000*1000 or larger. I know the package 'ltsa' which seems to use the Trench algorithm to compute the inverse of a Toeplitz matrix. I am looking for a so to say

Hi, Using indicator variables I have been able to fit and run the code for fitting a bivariate mixed model using unstructured covariance matrix The code is lme.fit1<- lme(one.var~-1+indic1+indic2+I(indic1*d.time)+I(indic2*d.time), random =~ -1+indic1+indic2|m.unit, weights = varIdent(~1|indic1) ,data = new.data) My variables are one.var :- the two response variables stacked one after

Hi, I have a bivariate longitudinal dataset. As an example say, i have the data frame with column names var1 var2 Unit time trt (trt represents the treatment) Now suppose I want to fit a joint model of the form for the *i* th unit var1jk = alpha1 + beta1*timejk + gamma1* trtjk + delta1* timejk:trtjk + error1jk var2 = alpha2 + beta2*timejk + gamma2* trtjk + delta2* timejk:trtjk +

Hello everybody, I recently wrote a "program" that to generate AR1 time series, here the code: #By Jomopo. Junio-2007, Leioa, Vizcaya #This program to create the AR1 syntetic series (one by one) #Where the mean is zero, but the variance of the serie AR1 and #the coef. of AR1 are be changed. If var serie AR1 = 1 then is standarized! #Final version for AR1 time series program #Mon Jul

Full_Name: Hao Yu Version: 1.4.1 OS: Windws and Linux Submission from: (NULL) (129.100.45.161) Hi, Recently we did some benchmarks regarding matrix inverse operation and found some strange things. See the following results (the package Matrix is most updated). 1. load the function Toeplitz and library(Matrix) "Toeplitz" function(x) { matrix(x[1 + abs(outer(seq(along = x),

[Apologies in advance if this is too "statistics" and not enough "R".] I've got an experiment with two sets of treatments. Each subject either received all treatments from set A or all treatments from set B. I can compute the N pairwise correlations for all treatments in either set using cor(). If I take the mean of these N pairwise correlations, I see that the effects

[Hope this is the right list where to send...] An attempt to update package 'mnormt' involves the addition of a small new function called 'pd.solve'. When I come to the package checking stage, an error occurs in parsing pd.solve.Rd. The full transcript of the outcome is copied below (it includes details on my installation) but the critical point is where the \examples{} section

Dear list, I have a problem on persp() x <- u1data #first coloum in attached data y <- u2data #second coloum in attached data f <- function(x,y){qgev(pnorm(rhoF*qnorm(pnorm((qnorm(y)-rho2*qnorm(x)/sqrt(1-rho2^2)))) +sqrt(1-rhoF^2)*qnorm(0.95)),-0.3935119, 0.4227890, 0.2701648)} z <- outer(x,y,f) persp(x,y,z) The R will display: "Error in persp.default(x, y,

Hello, I am updating my benchmark (http://www.sciviews.org/other/benchmark.htm) to recent versions of data analysis software (including R 1.6.0 and Splus 6.1), and I now run it on a Pentium IV instead of the old Celeron 500 Mhz that candidates for retirement. I test R under Windows Xp pro with and without optimized BLAS. I use the optimized Rblas.dll for P4 found on CRAN. Here are the results.

Hello, I'm quite new with R and so I would like to know if there is a command to calculate an integral. In particular I simulated a bivariate normal distribution using these simple lines: rbivnorm <- function(n, # sample size mux, # expected value of x muy, # expected value of Y sigmax, # standard deviation of

Fritz just put the first version of a new time series package to the contrib section at CRAN. The package is called "tseries.tgz" and provides a library for time series analysis. It contains acf Autocorrelation Function adf.test Augmented Dickey-Fuller Test amif Auto Mutual Information Function bds.test BDS Test

Fritz just put the first version of a new time series package to the contrib section at CRAN. The package is called "tseries.tgz" and provides a library for time series analysis. It contains acf Autocorrelation Function adf.test Augmented Dickey-Fuller Test amif Auto Mutual Information Function bds.test BDS Test

Hi All, I am doing econometric modeling of panel data (fixed effects). We currently use Eviews to do this, but I have discovered a bug in Eviews 7 and am exploring the use of R to build panel data models / longitudinal data models. I looked at the plm package but do not see how I can incorporate AR terms in the model using the plm package. I have an Eviews model with two AR terms, AR(1) and

Hi, I maintain a driver for a 10GbE nic which supports multiple hardware tx/rx rings. We can steer rx packets into rings using the "standard" NDIS6 Toeplitz hashing on TCP port numbers, IP addresses, etc. We can also steer packets based on MAC address. Would this NIC be considered to be capable of supporting crossbow? Also, can crossbow do things like steer outgoing packets to the