similar to: Graybill-Bowden confidence band

Hello. I'm trying to find a way in R to calculate between and within subject variances and confidence intervals for some analytical method development data. I've found a reference to a method in Burdick, R. K. & Graybill, F. A. 1992, Confidence Intervals on variance components, CRC Press. This example is for Balanced Data confidence interval calculation from Pg 62. The data are

Odd behaviour of function cor() in R-2.10.1-64bit-Unix In a dataset with 1366 patients and 244 clinical variables Spearman's Rho was calculated for some fatty acids and BMI and came over something rather odd: R seems to calculate Rho differently on 2.10.1-64bit-Unix and 2.9.0-32bit-Windows when I calculate the complete (244x244) correlation matrix and then pick out the values I am

Dear R community: I am trying to do a simulation study mentioned by Fu (1998), Journal of Computational and Graphical Statistics, Volume7, Number 3, Page 397-416. In order to give a clear statement of quesion I copy the following paragraph from the article: We compare the bridge model with the OLS, the lasso and the ridge in a simulation of a linear regression model of 30 observations and 10

Arrrrr, I think I've found a bug in the behavior of the stats::cor function when NAs are present, but in case I'm missing something, could you look over this example and let me know what you think: > a = c(1,3,NA,1,2) > b = c(1,2,1,1,4) > cor(a,b,method="spearman", use="complete.obs") [1] 0.8164966 > cor(a,b,method="spearman",

Two friend reported me a problem, which I can't solve: (I run R-1.0.0, Debian Linux) They hava a function "corr.matrix" (see end of mail), and when they create a 173x173 matrix with this function V <- corr.matrix(0.3, n=173) V1 <- qr.solve(V) reports: Error in qr(a, tol = tol) : NA/NaN/Inf in foreign function call (arg 1) For n < 173, qr.solve returns the correct

Based on simulations, I've come up with a simple function to compute the confidence interval for the variance of the binomial variance, where the true variance is v = rho*(1-rho)/n where rho = true probability of success and n = # of trials. For x = # successes observed in n trials, p = x / n as usual. For p < 0.25 or p > 0.75, I use the proportion-based transformed confidence

Hi all, I am doing a two-sided DW test: H0: rho = 0 H1: rho =/= 0 My understanding is that most test statistics tables are one-sided. It's the way they created the table. So from online, by doing Googling, I found a bunch of DW tables for Confidence Level 5%. Those tables can answer my two-sided question at 5x2 = 10% confidence level. But what if I want two-sided test at 1% and 5%

This amusing behaviour is from R2.6.1 on WinXP Pro SP2 running with boot.in= i /3GB flag, exploring memory limits. =20 When actual (object, not total) memory usage hits 2048 MB, memory.size star= ts counting down again, but reports a negative amount, e.g. -2046.333. Is t= his an intended (or unavoidable) feature?) =20 Thanks, =20 Rory Bowden bowden at stats.ox.ac.uk =20 [[alternative

I have been using the hetcor function in the polycor package. When I don't specify the use option everything runs smoothly. However, when I specify use either as "pairwise.complete.obs" or "complete.obs" I get this error Error in optim(rho, f, control = control, hessian = TRUE, method = "BFGS") : non-finite value supplied by optim Is this an error in

Hi: I have two time series y(t) and x(t). I want to regress Y on X. Because Y is a time series and may have autocorrelation such as AR(p), so it is not efficient to use OLS directly. The model I am trying to fit is like Y(t)=beta0+beta1*X(t)+rho*Y(t-1)+e(t) e(t) is iid normal random error. Anybody know whether there is a function in R can fit such models? The function can also let me specify

R-Experts, Here below my R code working without error message but I don't get the results I am expecting. Here is the result I get: [1] "All values of t are equal to 0.28611928397257 \n Cannot calculate confidence intervals" NULL If someone knows how to solve my problem, really appreciate. Best, S ######################################################### # Difference in Spearman

Hello R-users, I am using gls function in R to fit a model with certain correlation structure. The medol as: fit.a<-gls(y~1,data=test.data,correlation=corAR1(form=~1|aa),method="ML") mu<-summary(fit.a)$coefficient With the toy data I made to test, the estimate of mu is exactly equal to the overall mean of y which can not be true. But, if I make a toy data with y more than two

I believe the problem is here: cor1 <- cor(x1, y1, method="spearman") cor2 <- cor(x2, y2, method="spearman") The x's and y's are not looked for in data (i.e. NSE) but in the environment where the function was defined, which is standard evaluation. Change the above to: cor1 <- with(d, cor(x1, y1, method="spearman")) cor2 <- with(d, cor(x2, y2,

Hi, I have a dataset with four categories of data, the number of samples are not the same in each category. I want to find the Spearaman's Rho. Let me give an example. x=(14.22770439,26.49420624,46.7277932,19.02550707,23.37379361,16.97789862,19.77100085,23.11270162,13.72929843,33.54430621,14.4756979,70.15811106,11.22789833,NA,NA,NA)

http://bugzilla.mindrot.org/show_bug.cgi?id=521 Summary: PAM authentication not working in privilege seperation mode running in trusted system on hp-ux Product: Portable OpenSSH Version: 3.5p1 Platform: HPPA OS/Version: HP-UX Status: NEW Severity: major Priority: P2 Component: sshd

Hi I am trying to use the deriv and eval functions to obtain the value of a function , say "xi-(alpha0+alpha1*gi)" , differentiated with respect to alpha0 and alpha1, in the following way # for gi = 0 > dU1dtheta <- deriv(~ xi-(alpha0+alpha1*gi), c("alpha0","alpha1")) > eval(dU1dtheta) (Intercept) -0.2547153 attr(,"gradient")

Hi everyone. I have recently installed R 2.14.1 on my 64-bit Windows 7 laptop. I am attempting to include some favourite functions in the Rprofile.site file to run at R start-up as I did with my previous 32-bit XP machine. I have edited the Rprofile.site file in "C:\Program Files\R\R-2.14.1\etc\" but the added code doesn't seem to be executed when I run R, whether through Tinn-R

Hello, I am fitting data using different methods e.g. Local Polynomial and Smoothing splines. The data is generated out of a true function model with added normally distributed noise. I would like to know "how often the confidence band for all points simultaneously contain all true values". I can answer the question for one point in the following way: e.g. #

Hi, does anyone know how do I plot confidence intervals as a shaded band around a curve, rather than as errors bars? many thanks, ulisses. [[alternative HTML version deleted]]

I'm using the package 'locfit' for nonparametric regression. This package contains the function 'scb' to compute simultaneous confidence bands. The variance of the data is unknown. Up to now I compute a fit with 'locfit'. Afterwards an estimate of the residual variance is computed by the function 'rv'. The weights in the 'scb'-function are set 1/sigma^2