[R] P value discrepancy plots

Hello R-users, I am trying to plot P value discrepancy plots as describe by Russell Davidson and James G. MacKinnon in "Graphical Methods for Investigating the Size and Power of Hypothesis Tests (1998)". I know ecdf () to obtain the empirical cumulative distribution frequencies and knots() to extra

Re: [R] rbind in a loop with " : " elements

t > an example, is your real problem big? > > Hope this helps, > > Rui Barradas > > Em 22-08-2012 14:23, bilelsan escreveu: > > > Dear Ruser, > > Below, the deal (you can copy paste): > > > > r=3 ; set.seed(1)

[R] rbind in a loop with " : " elements

Dear Ruser, Below, the deal (you can copy paste): r=3 ; set.seed(1) v <- matrix(c(rnorm(40)),10,4) for (j in 1:4){ for (i in 1:r){ x <- t(v[,j]^(i)*v[,1:4]^((r-(4-1)):r)) print(x) } } How to reach to " x " " row bind " inside or outside (preferred) of the loop. T

Re: [R] taylor expansions with real vectors

Thanks for specifying the solution. The deal is that we are faced of vectors. Moreover I need to specify them as function of own-lagged with expansion=1,2, … ; lag=1, 2, … set.seed(1) E <- cbind(as.vector(rnorm(10)),as.vector(rnorm(10)),as.vector(rnorm(10))) #or more vectors; here 3 for illustra

Re: [R] taylor expansions with real vectors

Hi, Thanks a lot for answer. It is what I mean. But the code does not seem to work ( Le Jul 19, 2012 à 8:52 AM, Petr Savicky [via R] a écrit : > On Wed, Jul 18, 2012 at 06:02:27PM -0700, bilelsan wrote: > > Leave the Taylor expansion aside, how is it possible to compute with [R]:

Re: [R] taylor expansions with real vectors

Leave the Taylor expansion aside, how is it possible to compute with [R]: f(e) = e1 + e2 #for r = 1 + 1/2!*e1^2 + 1/2!*e2^2 + 1/2!*e1*e2 #for r = 2, excluding e2*e1 + 1/3!*e1^3 + 1/3!*e1^2*e2 + 1/3!*e2^2*e1 + 1/3!*e2^3 #for r = 3, excluding e2*e1^2 and e1*e2^2 + ... #for r = k In other words, I

Re: [R] taylor expansions with real vectors

Dear list, I have a big deal concerning the development of a Taylor expansion. require(Matrix) e1 <- as.vector(1:5) e2 <- as.vector(6:10) in order to obtain all the combinations between these two vectors following a Taylor expansion (or more simply through a Maclaurin series) for real numbe

Re: [R] the significance of BEKK estimation

Hi zoe, it's easy in a spreadsheet to calculate the p-value; estimates/stand.error = 1.96>5%<-1.96 for the asymmetry you must use: model=mGJR.est(eps1=#1, eps2=#2, order=c(1,1,1)) mvBEKK.diag(model) cheers -- View this message in context: http://r.789695.n4.nabble.com/the-significance-of-BEKK-e