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...d bit|Mode ID|LSP|OL pitch|OL Exc gain| --------------------------------------------------------------------------- Fine pitch1| --------------------------------------------------------------------------- Pitch gain1| --------------------------------------------------------------------------- Innovation gain1| --------------------------------------------------------------------------- Innovation VQ1| --------------------------------------------------------------------------- Fine pitch2| --------------------------------------------------------------------------- Pitch gain2| ----------...

...------------------------------------------------------ so.... like this: ---------------------------------------------------------------------------------- Wideband bit|Mode ID|LSP|OL pitch| ---------------------------------------------------------------------------------- Fine pitch1|Pitch gain1|Innovation gain1| Innovation VQ1| ---------------------------------------------------------------------------------- Subframe 1 content | ---------------------------------------------------------------------------------- Fine pitch2|Pitch gain2|Innovation gain2| Innovation VQ2| -------------------------------...

...ime, but it would have been nice to have it there from the first observation... I took a look into the code for arima.sim, and I think I found the reason for this behaviour in the line x <- ts(c(rand.gen(n.start, ...), innov[1:n]), start = 1 - n.start) It seems like the "warming up" innovations are standard normal, and that that's why the first observations of z0 are so large in magnitude. So one solution is to generate z0 <- arima.sim(list(ar=c(0.9)), n=n, innov=eps, sd=sd(eps)), but I didn't figure out this before having taken a look at the code. So my question is: Wouldn...

Just a reminder: AstriCon is coming up in October in Washington, DC (http://www.astricon.net/ ) and we're looking forward to seeing you there! We're getting to the deadline for Innovation Awards for this year. What's an Innovation Award? The Innovation Award is designed to recognize developers, customers and partners for outstanding achievements that are improving business processes, overcoming technology challenges and enhancing the company's bottom line. Digium...

...art=10) > x[1:10] [1] 3.194806 4.214894 5.168017 7.925152 8.810817 9.131695 [7] 7.521283 8.266911 8.923429 9.651293 > y[1:10] [1] -0.7202632 0.4564274 1.5598893 4.4613486 [5] 5.4855660 5.9394547 4.4567320 5.3249417 [9] 6.0991390 6.9399748 Given the fact that I have provided the innovations shouldn't the time series be exactly the same? Any help would be greatly appreciated. All the best, Sam. [[alternative HTML version deleted]]

Dear all, Can garch function fit also t-innovations or only Gaussian innovations? -- With kind regards -- Lepo pozdravljeni -- Gr??e (Gr?ezi) -- Gorazd Brumen ------------------------------- Mail 1: gbrumen at student.ethz.ch Mail 2: gorazd.brumen at fmf.uni-lj.si Tel.: +41 (0)1 63 34906 Homepage: valjhun.fmf.uni-lj.si/~brumen

Hi, I have been using arima.sim from the stats package recently, and I'm wondering why I get different results when using what seem to be the same parameters. For example, I've given examples of three different ways to run arima.sim with what I believe are the same parameters. It's my understanding from the R documentation that rnorm is the default function for rand.gen if not

...did Speex use the AR (Autoregressive) model or the ARMA model? 2. Am I right to say that Speex use a multistage VQ (since I believe Speex employs two or more VQ consecutively - based on the manual it says that Speex uses dynamically selectable codebooks (linear prediction,pitch prediction and innovation))? 3. It is said in the manual that Speex also use sub-vector fixed (innovation)codebooks, does this mean that it also utilises a Split VQ? 4. In the part about innovation codebook, it is said that the final excitation signal would be made up of the innovation signal and the pitch prediction,...

Hi, Following convention below: y(t) = Ax(t)+Bu(t)+eps(t) # observation eq x(t) = Cx(t-1)+Du(t)+eta(t) # state eq I modified the following routine (which I copied from: http://www.stat.pitt.edu/stoffer/tsa2/Rcode/Kall.R) to accommodate u(t), an exogenous input to the system. for (i in 2:N){ xp[[i]]=C%*%xf[[i-1]] Pp[[i]]=C%*%Pf[[i-1]]%*%t(C)+Q siginv=A[[i]]%*%Pp[[i]]%*%t(A[[i]])+R

...Implement strategy for promoting the broader utilization of innovative approaches across the development portfolio, through coordinated efforts involving clinical, operational, regulatory areas. Bring together key stakeholders from different key areas, identify potential hurdles for broader use of innovation in drug development and participate in finding solutions for them. Collaborate in talent identification for QDS group, hiring and development. Ensure focus on innovation is maintained in QDS group. • Evaluate and implement innovative approaches: participate in hands-on implementation of inn...

LLVM Developers, The compiler teams at the Qualcomm Innovation Center are hiring. In summary, we are doing interesting things with LLVM; come join us! I have included a more detailed description below. If you are interested, please contact me at adasgupt at quicinc.com -Anshu --- Opportunities at Qualcomm Innovation Center, Inc. Compiler Technologies Mobil...

...o that it never gets initialised at boot. Great! Shorewall still failed with the same error I''m at a loss... Eth1 is not in my interfaces file Eth1 is not enabled Yet Shorewall sees it and then objects... Please help! Cheers Jason Ward IT Manager Fundraising Innovations Ltd Incorporating firsthelpline.com, energyhelpline.com and switchandgive.com Tel: 020 7183 0484 Suite 9, 30 Great Guildford Street, London, SE1 0HS Compare ALL energy suppliers in one place and find a great deal on your home phone __________________________________________________...

...# and GARCH(1,1), # with normal conditional distribution functions. # # Author: # (C) 2002, Diethelm Wuertz, GPL # ############################################################################ #### # PART I: Estimation: # Settings: set.seed(547) # Bollerslev's GARCH(1,1) with normal innovations: model = list(omega = 1e-6, alpha = 0.1, beta = 0.8, mu = 0) x = garchSim(model, n = 1000) fit = garchFit(as.numeric(x), order = c(1, 1)) print(fit) # Summary and Diagnostic Analysis: summary(fit) # Plot Results: par(mfrow = c(2, 2)) plot(fit) ### Results of the estimations are false....

Hi This is my first post to this group, so apologies in advance if I get it wrong. I would like to know how the prediction for arima models works in R. I have a time series to which I fit an arima model, of varying AR and MA orders. I then use the predict function to project it forward. I have also written my own function to perform the prediction, but it gives different answers to Arima.predict

Dear useRs, I want to simulate a time series (stationary; the distribution of values is skewed to the right; quite a few ARMA absolute standardized residuals above 2 - about 8% of them). Is this the right way to do it? #-------------------------------- load("rdtb") #the time series > summary(rdtb) Min. 1st Qu. Median Mean 3rd Qu. Max. -1.11800 -0.65010 -0.09091

Hi all, I was in Las Vegas yesterday accepting an award from eWeek and PC Magazine on behalf of Samba for the Innovation in Infrastructure Award in the "Enterprise Software" catagory ! The award was sepcifically for Samba 2.2.2, and we beat out Sun Microsystems Java 2 Platform Standard Edition Version 1.4 and Bea Systems WebLogic Server 7.0 for the award, so I'm stunned that we won. These guys have mar...

Hi all, I was in Las Vegas yesterday accepting an award from eWeek and PC Magazine on behalf of Samba for the Innovation in Infrastructure Award in the "Enterprise Software" catagory ! The award was sepcifically for Samba 2.2.2, and we beat out Sun Microsystems Java 2 Platform Standard Edition Version 1.4 and Bea Systems WebLogic Server 7.0 for the award, so I'm stunned that we won. These guys have mar...

...think they are the same. Skew = 1 means no skewness (I can not find the paper defining the distribution). library(fSeries) curve(dsnorm(x, 0, 1, 1), -2, 2, add = F, col = 'red') #skew normal with skew 1 curve(dnorm(x, 0, 1), -2, 2, add = T, col = 'blue') #normal Then I try them as innovations, #normal innovation garch_norm <- garchFit(series = logr, include.mean = F) #skew normal innovation #this line do not include skew, so it got same result as normal garch_snorm <- garchFit(series = logr, cond.dist = 'dsnorm', include.mean = F, include.skew = F) #this line includes...

Dear Users, I would like to simulate an AR(1) (y_t=ct1+y_t-1+e_t) model in R where the innovations are supposed to follow a t-GARCH(1,1) proccess. By t-GARCH I want to mean that: e_t=n_t*sqrt(h_t) and h_t=ct2+a*(e_t)^2+b*h_t-1. where n_t is a random variable with t-Student distribution. If someone could give some guidelines, I can going developing the model. I did it in matlab, but the loo...

Dear useRs, we are organizing the following session Topic: Innovative Tools in Data Analysis Organizers: Achim Zeileis and Bettina Gruen at the First Workshop of the ERCIM Working Group on Computing & Statistics June 19-21, 2008 Neuchatel, Switzerland URL: http://www.dcs.bbk.ac.uk/ercim08 To improve the quality of statistical data analysis the provision of innovative tools which make new