similar to: hep on arithmetic covariance conversion to log-covariance

Dear All,   thanks to Berend, my question posted yesturday was solved succesfully here: http://r.789695.n4.nabble.com/hep-on-arithmetic-covariance-conversion-to-log-covariance-td4646068.html . I posted the question with the assumption of using the results with rlnorm.rplus() from compositions. Unfortunatelly, I am not getting reasonable enough outcome. Am I applying the results wrongfully? The

I have to calculate the logreturn variance in the Heston model. How can I do? Do you know some function that calculates it? Thank you Barbara -- ________________________________________________________ Le informazioni contenute in questo messaggio di posta elettronica sono strettamente riservate e indirizzate esclusivamente al destinatario. Si prega di non leggere, fare copia, inoltrare a

Hi all i have two data sets, spot and futures cash market prices. to estimate the minimum variance hedge ratio, i first had a glance on the correlation coefficient of relative price change (ln(St / St-1). surprizingly the value is just 0.2 compared to actual price correlation of 0.9. (i did regress the spot change on future change, co-effi is 0.3, and R2 is only 0.025 a) in such scenario can

Hi I have generate two variable with uniform disrtribution A and B and I want to calculate the number of cases where B<A^2 So I done it by sum(B<A^2), but I'm not sure if there is anther way to calculate the number of cases in the distribution or what I have done is fine thanks for helping me Woo -- View this message in context:

Hi, I created a package for OpenSSH 3.7.1p2 in UNIX (OS: Sun Solaris), the newly created package includes binaries,man pages, libraries and Configuration files. I am planning to install this package in all of my Sun server's (Approximately 200 Server's). We have SSH/OpenSSH older version are already installed and running in all of the sun boxes. I want to install the

Dear friends, I met some problem on using GAM() function in R. Any help or suggestions are greatly appreciated. # My programs and problems are list below# library(splines) library(gam) point<-read.csv("d:/gam.csv",sep=",",header=TRUE) #read the data gam.opt<-gam(mark~lo(x,y,span=0.2)+lo(lstday2004,span=0.2)+lo(slope,span=0.2)+lo(ndvi2004,span=

Hello, On a newly built Asterisk 13.13.1 system, I can't make HEP work with chan_sip (though I could make it work with PJSIP on another instance). Looking either at [1] or hep.conf, I can't see anything meaning HEP requires PJSIP. Before diging deeper, may I simply ask if HEP requires PJSIP or not ? What about a line mentioning the answer in above documents (to keep other from wondering

Dear R users, I?d like to pose aquestion about pMCMC and HDP. I have performed a mixed logistic regression by MCMCglmm (a very good package) obtaining the following results: Iterations = 250001:799901 Thinning interval = 100 Sample size = 5500 DIC: 10.17416 G-structure: ~ID_an post.mean l-95% CI u-95% CIeff.samp ID_an 0.7023 0.0001367 3.678 2126 R-structure: ~units post.mean l-95%

Dear all,   I did ANOVA for many response variables (Var1, Var2, ....Var75000), and i got the result of p-value like below. Now, I want to select those predictors, which have pvalue less than or equal to 0.05 for each response variable. For example, X1, X2, X3, X4, X5 and X6 in case of Var1, and similarly, X1, X2.......X5 in case of Var2, only X1 in case of Var3 and none of the predictors in case

Hi All I am getting the above mentioned error when I run the code below. I don't know why because I have implemented the function and I'm calling the function with a parameter. I'm obviously missing the plot ... Can someone perhaps point out the error of my ways? Error: > out<-ode(y=init, times=times, func=G1999, parms=parms, method="lsoda") Error in m_Na(v) : attempt

Dear R-help members, Apologies - I am posting on behalf of a colleague, who is a little puzzled as STATA and R seem to be yielding different survival estimates for the same dataset when treating a variable as ordinal. Ordered() is used to represent an ordinal variable) I understand that R's coxph (by default) uses the Efron approximation, whereas STATA uses (by default) the Breslow. but we

Hi, I need to subset different levels of vector in a dataset to create a new dataframe that contains only these. These observations are not numerical, so I can't use the subset() function (at least this is the response I get from R). Suppose the dataframe looks like this:   ParticipID    ERP   Electrode 1         s1  0.0370       FP1 2         s2 35.0654       FP2 3         s3

Dear all, I'm using R 2.8.1 under Windows Vista on a dual core 2,4 GhZ with 4 GB of RAM. I'm trying to reproduce a result out of "Analysis of Financial Time Series" by Ruey Tsay. In R I'm using the fGarch library. After fitting a ar(3)-garch(1,1)-model > model<-garchFit(~arma(3,0)+garch(1,1), analyse) I'm saving the results via > result<-model

Dear Dr.Goslee and anyone may intrested in matrix manipulate, I am using your ecodist to do mantel and partial mantel test, I have locality data and shape variation data, and the two distance matrixs are given as belowings. When I run the analysis, it is always report that the matrix is not square, but I didn't know what's wrong with my data. Would you please help me on this. I am quite

Hello list I'm a little confused about the R2 and adjusted R2 values reported by lm() when I try to fix an intercept. When using +0 or -1 in the formula I have found that the standard error generally increases (as I would expect) but the R2 also increases (which seems counter intuitive). I've pasted a short test script below to illustrate. I do realise that many will say I shouldn't be

Hi R users, I have a problem in downloading Yahoo Finance data from R. I have tried an example given in R, to download. The error is given below: >library(fCalendar) > yahooImport("s=IBM&a=11&b=1&c=1999&d=0&q=31&f=2000&z=IBM&x=.csv ", file = "D:\\ Downlaod",source = "http://ichart.yahoo.com/table.csv?", save = FALSE,

mgcv: Constructing probabilities for binomial GAM with crossed random intercepts and factor by variable Hello, (I'm sorry if this has been discussed elsewhere; I may not have been looking in the right places.) I ran a binomial GAM in which "Correct" is modelled in terms of the participant's age and the modality in which the stimulus is presented (written vs spoken).

Hi, I have two matrices, A (axd) and B (bxd). I want to get another matrix C (axb) such that, C[i,j] is the Euclidean distance between the ith row of A and jth row of B. In general, I can say that C[i,j] = some.function (A[i,], B[j,]). What is the best method for doing so? (assume a < b) I have been doing some exploration myself: Consider the following function: get.f, in which,

Hi, I am trying to construct a logistic regression model from my data (104 patients and 25 events). I build a full model consisting of five predictors with the use of penalization by rms package (lrm, pentrace etc) because of events per variable issue. Then, I tried to approximate the full model by step-down technique predicting L from all of the componet variables using ordinary least squares

A big compile time regression. Any ideas? Ciao, Duncan. On 22/07/11 19:13, llvm-testresults at cs.uiuc.edu wrote: > > bwilson__llvm-gcc_PROD__i386 nightly tester results > > URL http://llvm.org/perf/db_default/simple/nts/253/ > Nickname bwilson__llvm-gcc_PROD__i386:4 > Name curlew.apple.com > > Run ID Order Start Time End Time > Current 253 0 2011-07-22 16:22:04