similar to: Testing volatility cluster (heteroscedasticity) in stock return?

Helloo, i have measure VaR with time dependen volatility (GARCH) and now want to measure expected shortfall (ES) using cornish fisher expansion (cause non-normal distribution), but i have limitedness about using R. Could you help me, how measure that ES with cornish fisher expansion using R.... i really need your help. thank you for the attention. Regards Eko [[alternative HTML version

?haiii i want to know, is there?any script in R to measure looping averageif (like in the excel) ....... for example: i have a vector row????value 1????????0 2????????2 3????????-3 4????????-2 5????????1 6????????-2 i want to measure the average of the vector for negative value with window estimation 5 so first mean is (-3+-2)/2 ???? second mean is (-3+-2+-2)/3??

Hi everyone Is rubytorrent work on windows XP. I have problem for using it. Here my Configuration OS: Windows XP Ruby Version: 1.8.2 Already Install Azureus and ABC torrent. I manage to set Azerus behave as tracker that listen to IP 127.0.0.1 and seeding file from "\ekobudi\bittorrent\host0". After that I copy torrent file from"\ekobudi\bittorent\host0" to"

If you don't get a response it is because you did not read the Posting Guide which indicates that the R-sig-ME mailing list is where this question would have been on-topic. -- Sent from my phone. Please excuse my brevity. On August 16, 2017 6:17:03 AM PDT, b88207001 at ntu.edu.tw wrote: >Hello dear uesRs, > >I am working on modeling both level one and level two

A better place for this post would be on R's mixed models list: r-sig-mixed-models . Cheers, Bert Bert Gunter "The trouble with having an open mind is that people keep coming along and sticking things into it." -- Opus (aka Berkeley Breathed in his "Bloom County" comic strip ) On Wed, Aug 16, 2017 at 6:17 AM, <b88207001 at ntu.edu.tw> wrote: > Hello dear

Hello dear uesRs, I am working on modeling both level one and level two heteroscedasticity in HLM. In my model, both error variance and variance of random intercept / random slope are affected by some level two variables. I found that nlme is able to model heteroscedasticity. I learned how to use it for level one heteroscedasticity but don't know how to use it to model the level

Hi, I am currently trying to do a GLMM on a dataset with percent cover of seagrass (dep. var) and a suite of explanatory variables including algal (AC) and epiphyte cover (EC), rainfall, temperature and sunshine hours. M2=glmer(SG~AC+EC+TP+SS+RF+(1|Location/fSi/fTr), family=binomial,data=data,nAGQ=1) As the dependent variable is percent cover, I used a binomial error structure. I also have a

Dear all, Sorry if this is too obvious. I am trying to fit my multiple regression model using lm() Before starting model simplification using step() I checked whether the model presented heteroscedasticity with ncv.test() from the CAR package. It presents it. I want to correct for it, I used hccm() from the CAR package as well and got the Heteroscedasticity-Corrected Covariance Matrix. I am not

Already try the pre realease 0.3. The rtpeer.rb is working. But I don''t know why is take quite a while to listen only port 6969. The after that start to scan port 6881,6882..etc. After that manage to download the file normally. As usual I run everything in one PC. Azureus, ABC, and rubytorrent. The example on "doc\api.txt" still doesn''t work for me. I am very hapy the

Dear altogether, is it possible to integrate "weights" arguments within lmer to incorporate statements to handle heteroscedasticity as it is possible with lme? I searched the R-archive but found nothing, insofer I assume it is not possible, but as lmer is under heavy develpoment, maybe something changed or is solved differently. Thus my question: While encountering heavy

To detect heteroscedasticity for a multiple linear OLS regression (no time dependencies): What if the residuals vs. fitted values plot shows well behaved residuals (cloud) - but the some of the x versus residuals plots are a megaphone? Also, it seems that textbooks and internet tutorials in R do not agree what is the best plot for detecting heteroscedasticity. What do you use? I found so

Hello, I have just recently started using R and was wondering whether anybody had a code written for White's heteroscedasticity correction for standard errors. Also, can anybody share a code for the GARCH(1,1) and GARCH-in-mean models for modelling regression residuals? Thanks a lot in advance, Spyros --------------------------------- [[alternative HTML version

Hi, I would like to generate two correlated variables. I found that funktion for doing that: a <- rmvnorm(n=10000,mean=c(20,20),sigma=matrix(c(5,0.8*sqrt(50), 0.8*sqrt(50),10),2,2)) (using library(mvtnorm)) Now I also want to generate two correlated variables where the error variance vary over the variable-correlation. And I want to plot this for showing heteroscedasticity. Like shown

Hi I am actually running the White test for correcting Heteroscedasticity. I used sandwich() & car(), however the output shows the updated t test of coefficients, with revised Standard Errors, however the estimates remained same. My problem is that the residuals formed a pattern in the original regression equation. After running the White's test, I got some new standard errors - but

Your understanding isn't similar to mine. Mine says robust/resistant methods are for data with heavy tails, not heteroscedasticity. The common ways to approach heteroscedasticity are transformation and weighting. The first is easy and usually quite effective for dose-response data. The second is not much harder. Both can be done in R with nls(). Andy From: Quin Wills > > I am

Dear lmer users, The experiment includes 15 groups of (3 males and 1 female). The female is characterized by its quality Q1 and Q2. Each male of a group is characterized by the number of MatingAttempts (with Poisson distribution). I want to examine if male mating attempts depend on female quality. I can see from graphic exploration that the within-group heterogeneity of male attempts increases

Hi there, Does anyone know of a statistical test for heteroscedasticity for an object of class "gls"? (or alternative objective methods). Thanks in advance, Ben Gillespie, Research Postgraduate o-------------------------------------------------------------------o School of Geography, University of Leeds, Leeds, LS2 9JT o-------------------------------o http://www.geog.leeds.ac.uk/

Hello, First, sorry for my poor english, I will try to be understood. It's the first time I try this "r-help mailing list" and I hope it will be a success. I am working on heteroscedasticity analysis. I would like to get the "Box-Ljung" and the "Lagrange multipliers" test. I found the first one in the library "ts", but I can't find the second one.

Hi everybody, I'm trying to analyse a set of data with a non-normal response, 2 fixed effects and 1 nested random effect with strong heteroscedasticity in the model. I planned to use the function lmer : lmer(resp~var1*var2 + (1|rand)) and then use permutations based on the t-statistic given by lmer to get p-values. 1/ Is it a correct way to obtain p-values for my variables ? (see below)

Dear all, I have been upgrade from samba 3.0.2a-1 to samba 3.0.5-2, login to samba from windows client ok, but the sharing printer was not working, also the file sharing, it looks like windows give the error the sharing cannot be found. To solve this i return back to 3.0.2a-1, and everything working fine again. Is it bug or not ? Anyone have experience regarding to upgrade 3.0.5-2 ? Regards