similar to: qr.solve (fwd)

Dear list, I am trying to replicate an econometrics study that was orginally done in Stata. (Blanton and Blanton. 2009. A Sectoral Analysis of Human Rights and FDI: Does Industry Type Matter? International Studies Quarterley 53 (2):469 - 493.) The model I try to replicate is in Stata given as xtpcse total_FDI lag_total ciri human_cap worker_rts polity_4 market income econ_growth log_trade

i want to ask 2 questions. 1) can R do Random-effects GLS regression which i can get from Stata? the following result is frome Stata.can I get the alike result from R? xtreg lwage educ black hisp exper expersq married union, re Random-effects GLS regression Number of obs = 4360 Group variable (i) : nr Number of groups = 545 R-sq:

Dear r-helpers, I can run the examples on the mcsamp help page. For example: **************************************** > M1 <- lmer (y1 ~ x + (1|group)) > (M1.sim <- mcsamp (M1)) fit using lmer, 3 chains, each with 1000 iterations (first 500 discarded) n.sims = 1500 iterations saved mean sd 2.5% 25% 50% 75% 97.5% Rhat n.eff beta.(Intercept)

> myfit1 <- gls(col1 ~ col2+col3+col4+col5+col6-1, data=data2, corr=corAR1( 0.3202), method='ML') Error: cannot allocate vector of size 199712 Kb if I get rid of the "corr=corAR1(0.3202)" option, it works okay... can anybody help me? thanks a lot! [[alternative HTML version deleted]]

How does one coerce predict.gls to incorporate the fitted correlation structure from the gls object into predictions? In the example below the AR(1) process with phi=0.545 is not used with predict.gls. Is there another function that does this? I'm going to want to fit a few dozen models varying in order from AR(1) to AR(3) and would like to look at the fits with the correlation structure

Hi, all: Two examples are shown below. I want to use the multiple comparison of Dunnett. It succeeded in upper case "example 1". However, the lower case "example 2" went wrong. In "example 2", the function pmvt return NaN, so I cannot show this simtest result. Is there any solution? (I changed the variable "maxpts" to a large number in front of the

I'm implementing a function to compute the moore-penrose inverse, using a code from the article: Fast Computation of Moore-Penrose Inverse Matrices. Neural Information Processing - Letters and Reviews. Vol.8, No.2, August 2005 However, the R presents an error message when I use the geninv. The odd thing is that the error occurs for some arrays, however they have the same size. And the R

Dear List, After running a compound symmetric model using gls, I realized that the default contrasts were not the ones that made the most sense given the biological relationships among the factor levels. When I either changed the factor levels to re-arrange the order they occur in the gls model (not shown below) OR specifically change the contrasts I get the exact same estimates for the

I am trying to run the following function (a hierarchical bayes linear model) and receive the error in solve.default. The function was originally written for an older version of SPlus. Can anyone give me some insights into where the problem is? Thanks R 2.4.1 on MAC OSX 2mb ram Mark Grant markg at uic.edu > attach(Aspirin.frame) > hblm(Diff ~ 1, s = SE) Error in solve.default(R, rinv)

Hello listmembers, I've been thinking of using gls in the nlme package to test for serial correlation in my data set. I've simulated a sample data set and have found a large discrepancy in the results I get when using the default method REML vs. ML. The data set involves a response that is measured twice a day (once for each level of a treatment factor). In my simulated data set, I

Hello useRs, I`m running structural equation models with R, but for one of my models the below error message apears. I`m trying to change startvalues but without success. The manual for sem package did not help me. Does anyone knows how to change startvalues for iteration in sem package? Or it can be another problem with the model? Error in startvalues(S, ram, debug = debug, tol = start.tol)

Dear R users, Does the results below make any sense? Can the the interval of the correlation coefficient be between *-1.0185* and -0.8265 at 95% confidence level? Liviu > library(boot) > data(mtcars) > with(mtcars, cor.test(mpg, wt, met="spearman")) Spearman's rank correlation rho data: mpg and wt S = 10292, p-value = 1.488e-11 alternative hypothesis: true rho is not

I am using the gls function of the nlme package to analyze data sets of soil respiration which have the following design: 3 complete blocks x 5 sampling dates (time from fertilization) x 3 fertilization levels. The fertilization dates are equal for all subjects (blocks) but not periodical (-46, 10, 24, 53, 123 days from the event). The code that I've been using is: fit.csnC<- gls(dno.C

Hi. I am attempting to run my code to get estimates for a nonlinear model. Unfortunately, when I run the code, I keep getting the following errors (they switch back and forth depending on when I run it): Error in nlsModel(formula, mf, start, wts) : singular gradient matrix at initial parameter estimates Error in nls(ywt_vib ~ weightfunc_vib(time_vib, Wmax_star, tau_star, gamma_star,

Hi all, I have a function rho.f which gives a list of estimators. I have the following problems. rho.f(0.3) gives me the right answer. However, if I use rho.f(corr[4]) give me a different answer, even though corr[4]==0.3. This prevents me from using a for loop. Can someone give me some help? Thank you very much in advance. Hannah >

Dear R-users I am relatively new to R, i hope my many novice questions are welcome. I have problems accessing some objects (specifically the random effects, correlation structure and variance function) from an object of class gls and lme. I used the following models: yah <- gls (outcome~ -1 + as.factor(Trial):as.factor(endpoint)+

Hello! I am trying to put two math expressions in the title of a plot. As you can see below, I can place correctly one expression at a time, but not both. Ideally I would like to have them separated by a comma. Any suggestions? > k <- 1 > n.eff <- c(20, 30) > ### this works > plot(0,0, main = substitute(n == k, list(k = k))) > ### this works > plot(0,0, main =

Hi, can anyone help me with the following code? Thanks! library(mvtnorm) f2 <- function(n, rho) { var <- matrix(c(1,rho,rho,1), nrow=2, ncol=2, byrow=T) beta <- seq(0, 1, length.out=n+1) alpha <- sort (sapply(1-beta, qnorm)) x <- array(0, dim=c(n, n)) for (s in 1:n) { for (t in 1:n){ if (s>=t) x[s,t] <- pmvnorm(lower=c(alpha[s],

Hello list, I've seen the recent discussions documenting problems with lm. I have encountered the following problem. I use WinXP Pro with service pack 1, and R 1.9.0, on a XEON 2GHz, with 1GB of RAM. > eff.fro std.dev mean NSTRDSP 7.403749e-01 1.215686e-01 CPFGEP 9.056763e+00 1.815686e+00 WSWOLF 4.703588e+05 1.112832e+05 NPILGRIM 1.017640e+06 2.134335e+05

hi, - big and ugly mail. If you don't like them, delete it now :-) - I have collected and classified some information of: http://home.earthlink.net/~rwhron/kernel/bigbox.html And I observed that ext3 performance is worse than previous kernels(2.4.19...). -ac and -aa are here only as reference. Complete information is in the upper URL. dbench: Performance is worse. dbench (Numbers are in