similar to: urppTest Z-tau? Z-alpha?

Dear List, How do I pick the p-value out of the urppTest result? For adfTest the p-value can be extracted by A2 at test$p.value following A2 <- adfTest(myData[,i], lags=2, type=c("c")) What do I do for urppTest? The above doesn't seem to work. There is a slot @test with $output, which is a list of various test results that didn't want to give away only the p-value

Hello all, I would like to carry out a single-equation approach of the Error Correction Model such as Delta_y(t) = a + b*y(t-1) + c*x1(t-1) + d*x2(t-1) + e*delta_x1(t) + f*delta_x2(t) + epsilon(t) Where, a, b, c, d, e, f are coefficients to be estimated, y is the dependent variable, and x1, x2 are independent variables. For the single equation approach of ECM, there is a requirement of the

I feel bad even asking, but: Rgames> data(OrchardSprays) Rgames> model<-lm(decrease~.,data=OrchardSprays) Rgames> model Call: lm(formula = decrease ~ ., data = OrchardSprays) Coefficients: (Intercept) rowpos colpos treatmentB treatmentC 22.705 -2.784 -1.234 3.000 20.625 treatmentD treatmentE treatmentF treatmentG treatmentH

How can I get the log odds associated with the levels in strata() within a clogit() model? I'm running R-1.9.0 on a Linux platform. I am using clogit() to run a Rasch model in Item Response Theory in psychometrics. Symbolically, the model is: logit(p_{j,k}) = \log({\Pr(p_{j,k}) \over \Pr(1-p_{j,k})}) = \theta_j - \alpha_k, That is, the log odds of answering an test item correctly is

I am trying to fit a linear mixed model of the form y_ij = X_ij \beta + delta_i + e_ij where e_ij ~N(0,s^2_ij) with s_ij known and delta_i~N(0,tau^2) I looked at the ecme routine in package:pan, but this routine does not allow for different Vi (variance covariance matrix of the e_i vector) matrices for each cluster. Is there an easy way to fit this model in R or should I bite the bullet and

Hallo everybody, I'm new in r and I"ll appreciate some help! I have a matrix of nrow=30 and ncoll=54,and I would like to generate 50 simulations with tha same size of the matrix!!!That is to say that I want to generate 50 matrices -for my 50 simulations - with the same dimensions! I took my 1st matrix according to the formula that I want to implement: D<-mean_m + U_i*mat_DELTA

Hi, I'm trying to fit the following model to data using 'nls': y = alpha_1 * beta_1 * exp(-beta_1 * x) + alpha_2 * beta_2 * exp(-beta_2 * x) and the call I've been using is: nls(y ~ alpha_1 * beta_1 * exp(-beta_1 * x) + alpha_2 * beta_2 * exp(-beta_2 * x), start=list(alpha_1=4, alpha_2=2, beta_1=3.5, beta_2=2.5), trace=TRUE, control=nls.control(maxiter =

Hello, I'm trying to fit a special kind of proportional odds model from: Whitehead et al. (2001). Meta-analysis of ordinal outcome using individual patient data. Statistics in medicine 20: 2243-2260. (model 2) The data are as follows: library(nlme) library(geepack) library(Design) library(MASS) options(contrasts=c("contr.SAS","contr.poly")) counts <-

Hi, as i suppose to know in a stationary GARCH(1,1) model the sum of alpha and beta has to be smaller than 1. But if i use the garchfit() function from the package fGarch for my timeseries the sum is bigger than 1. The adf.test tells me a p-value smaller than 0.01 instead. What does this mean for me? Can i trust in the coefficients in this case? mfg user84 -- View this message in context:

Dear all, I am doing a simulation for my model that works when I use only the rq() command. However, since I need to use the varcov matrix for my Wald test, I need to compute summary(rq(), cov=TRUE). But the simulation does not work because of the error: tau + h > 1: error in summary.rq I tried to use: if (tau + h > 1) stop("tau + h > 1: error in summary.rq") But the

hi, i have 2 lists of ranks for which i'd like to compute kendall tau. there are ties in the ranks which (to the best of my knowledge) means i cant use tau a but rather b or c. how does R handle that? are ties automatically detected (using corr.test()) and is tau b/c computed instead of tau a? also kendall does not work when values in list 1 do not occur in list 2 (and vice versa) - how does

Hi I need to know which package in R calculates the Goodman Kruskal's tau statistic for nominal data. Also is there any implementation for multiple classification analysis (Andrews at al 1973) in R? Any information on this would be greatly appreciated. Thank you Upasna -- --------------------------------------------------------------------- Upasna Sharma Research Scholar Shailesh J. Mehta

Hi, I would like to fit the following model with quantile regression: y ~ alpha + beta where both alpha and beta are factors. The conceptual model I have in my head is that alpha is a constant set of values, that should be independent of the quantile, tau and that all of the variability arises due to beta. If I just fit the model using the quantreg package like so: mdl <- rq( y ~ alpha

Full_Name: Dan Field Version: 1.6.2 OS: N/A Submission from: (NULL) (209.115.168.187) In kendall.c (library is ctest), the limits for the first loop in routine kendall_tau run from 0 through n-1, and the inner loop runs from 0 through i-1. This causes the each pair at index i to be compared with itself; my understanding is that there should only be n*(n-1)/2 pairs under consideration for

I have 3 variables relating to the successful introductions of species to 95 different areas: introduction frequency; number of successes pre 1906; number of successes post 1906 The data are not normal, nor homo-skedatic, so I am using non-parametric statistics. I have calculated Kendall's tau between both introduction & successes pre 1906 (tau=0.3903) and introduction & successes

Hi everybody, I am reading the Lomb paper (Lomb, 1976) and I found an interesting equation, and I wish to resolve it using R. I am wondering if anybody has a hint. The equation is: Yis[i] = a*cos((2*pi/T)*(Times[i] - Tau)) + b*sin((2*pi/T)*(Times[i] - Tau)) ... (1) Where T and Tau are constants. I know the "Times" and "Tis" values (in fact these values come from a Time

I would like to use greek "tau" as a symbol of variable to integrate over in plotmath expression(integral(f(tau)*dtau, 0,t)) but nothing seems to work. I tried d{\tau}, d\tau, etc., without any success Is it possible? How can I accomplish this? Best regards, Ryszard -------------------------------------------------------------------------- Confidentiality Notice: This message is

Dear I estimate a sample selection model using the Clayton copula and Burr and Gaussian marginal. I need to derive ther Kendall'sw tau from the concordance coefficient by integration. I came across a way to do that in R long time ago but cannot find it again. Can somewone tell me what to read and what to use? Thank you. Steven Yen

I discovered that the Kendall's tau calculation in R uses all pairwise comparisons which is O(n^2) and takes a long time for large vectors. I implemented a O(n*log(n)) algorithm based on merge-sort. Is this of interest to be included in core R? The code (fortran and R wrapper) is available in my package clinfun v0.9.7 (not exported in NAMESPACE). Thanks, Venkat -- Venkatraman E. Seshan,

Hi all, I would like to ask a question related to Kendall package. I ran Kendall (x,y) and saw the results. But I am not sure which tau values R reported. I have ties in my data set, so I want tau-b. Can anybody tell how Kendall package is calculating tau values? I have looked at the package PDF, but I could not find any useful information. As long as I see from the following link, there