similar to: [R-SIG-Finance] EM algorithm with R manually implemented?

Hi, I am trying to write the Realized GARCH model with order (1,1) The model can be describe bellow: r_t = sqrt( h_t) * z_t logh_t = w + b*logh_(t-1) + r*logx_(t-1) logx_t = c + q*logh_t + t1*z_t +t2*(z_t ^2 -1) + u_t and z follow N(0,1) , u follow N(0, sigma.u^2) But I'm troubled with the simulation check for my code. After I simulate data from the model and estimate the data, I

Dear R listers, I am learning the MLE utility optim() in R to program ordered logit models just as an exercise. See below I have three independent variables, x1, x2, and x3. Y is coded as ordinal from 1 to 4. Y is not yet a factor variable here. The ordered logit model satisfies the parallel regression assumption. The following codes can run through, but results were totally different from what I

Why fails nls with "singular gradient" here? I post a minimal example on the bottom and would be very happy if someone could help me. Kind regards, ########### # define some constants smallc <- 0.0001 t <- seq(0,1,0.001) t0 <- 0.5 tau1 <- 0.02 # generate yy(t) yy <- 1/2 * ( 1- tanh((t - t0)/smallc) * exp(-t / tau1) ) + rnorm(length(t))*0.01 # show the curve

Hi All, I'm new to R and am trying to run a unit root test on the vector "y" (a time series of inflation (i.e. changes in the Consumer Price Index quarter on quarter)). I've run the Augmented-Dickey-Fuller Test below (R's URCA package). It gives me an error that it cannot find the function ur.df unless I comment out the third last line of code (see below). I try to call

Hello, I have written a small function ('JostD' based upon a recent molecular ecology paper) to calculate genetic distance between populations (columns in my data set). As I have it now I have to tell it which 2 columns to use (X, Y). I would like it to automatically calculate 'JostD' for all combinations of columns, perhaps returning a matrix of distances. Thanks for any help

Hi everybody, I try to simulate random numbers from a trivariate nested Archimedean copula. My aim is to correlate two processes with, e.g. theta2, as the so called child pair and then to correlate these two processes with a third one with theta1 (parent). This "figure" tries to capture what I am explaining theta1 theta2

I fitted a gaussian mixture to my financial data. The data can be found here: http://uploadeasy.net/upload/32xzq.rar I look at the density with plot(density(dat),col="red",lwd=2) this has a skew of library(e1071) skewness(dat) -0.1284311 Now, I fit a gaussian mixture according to: f(l)=πϕ(l;μ1,σ21)+(1−π)ϕ(l;μ2,σ22) with:

Hi R User, I was trying to use R for WINBUGS using following model and data (example), but I am new with WINBUGS and don't know how we perform the analysis. I wonder whether I can run the following the example data and Winbugs Model in R. Your help will be highly appreciated. Sincerely, SN PANDIT === library(R2WinBUGS) #Model model{ #likelihood for(i in 1:N){ a1[i] ~ dnorm(a11[i],tau)

Hi R User, I was trying to use R for WINBUGS using following model and data (example), but I am new with WINBUGS and don't know how we perform the analysis. I wonder whether I can run the following the example data and Winbugs Model in R. Your help will be highly appreciated. Sincerely, SN PANDIT === library(R2WinBUGS) #Model model{ #likelihood for(i in 1:N){ a1[i] ~ dnorm(a11[i],tau)

A student brought this question to me and I can't find any articles or examples that are directly on point. Suppose there are 2 ordinal logistic regression models, and one wants to set them into a simultaneous equation framework. Y1 might be a 4 category scale about how much the respondent likes the American Flag and Y2 might be how much the respondent likes the Republican Party in America.

I?m trying to run a logistic joinpoint regression utilising the ljr package. I?ve been using the forward selection technique to get the number of knots for the analysis, but I?m uncertain as to my results and the interpretation. The documentation is rather brief ( in the package and the stats in medicine article is quite technical) and without any good examples. At the moment I?m thinking 1)find

Dear List, I am trying to estimate a 3 dimensional density through the DPpackage. For example # model sigma <- matrix(c(0.1,0.05,0.05,0.05,0.1,0.05,0.05,0.05,0.1), ncol=3) rnormm<- rmvnorm(n=100, mean=c(5,100,150), sigma=sigma) sigma2 <- matrix(c(10,0.05,0.05,0.05,10,0.05,0.05,0.05,10), ncol=3) rnormm2<- rmvnorm(n=100, mean=c(20,1,110), sigma=sigma) rnormm<-rbind(rnormm,rnormm2)

Hi, I'm new to the glm and logit world... and I'm reading some lecture notes and examples. I would like to try and generate the same result in R.. but I don't seem to be able to find the proper way to specify the formula.... let's say i have Desire Using Drugs Not Using Drugs Yes 219 753 No 288 347 Desire

In vorbis/lib/mdct.h the following are defined: for integer: #define TRIGBITS 14 #define cPI3_8 6270 #define cPI2_8 11585 #define cPI1_8 15137 #define FLOAT_CONV(x) ((int)((x)*(1<<TRIGBITS)+.5)) for floats: #define cPI3_8 .38268343236508977175F #define cPI2_8 .70710678118654752441F #define cPI1_8 .92387953251128675613F #define FLOAT_CONV(x) = x Could someone explain where these values

Hi I need to find the Hessian matrix for a complicated function from a certain kind of data but i keep getting this error Error in f1 - f2 : non-numeric argument to binary operator the data is given by U<-runif(n) Us<-sort(U) tau1<- 2 F1tau<- pgamma((tau1/theta1),shape,1) N1<-sum(Us<F1tau) X1<- Us[1:N1]

Hello, I am writing codes for time series computation but encountering some problems Given the quarterly data from 1983Q1 to 1984Q2 PI1<-ts(c(2.747365190,2.791594762, -0.009953715, -0.015059485, -1.190061246, -0.553031799, 0.686874720, 0.953911035), start=c(1983,1), frequency=4) > PI1 Qtr1 Qtr2 Qtr3 Qtr4 1983 2.747365190 2.791594762

At 01:37 PM 5/10/00 +0200, ralle wrote: >Hi, >I have a problem understanding what is going on with eigen() for >nonsymmetric matrices. >Example: >h<-rnorm(6) >> dim(h)<-c(2,3) >> c<-rnorm(6) "c" is not a great choice of identifier! >> dim(c)<-c(3,2) >> Pi<-h %*% c >> eigen(Pi)$values >[1] 1.56216542 0.07147773 These could

Dear R-users, Hereby a polar plot function for plotting angular data. I hope it will be usefull for some of you. I had a need to plot frequencies of wind-directions. The not-that-cheap SigmaPlot software did not allow me to change the orientation of the angular axis to clockwise orientation (what is used for meteorological observations). I even tried the latest version availible at the time

Im tryng to understand an error i get with integrate. this is 1.7.0 on solaris 2.8. ##i am trying to approximate an integral of this function, f<-function(b) exp(-(b-mu)^2/(2*tau2))/(p-exp(b))*10^6 ##with tau2 <- .005;mu <- 7.96;p <- 2000 ##from -inf to different upper limits. using integrate(f,-Inf,log(p-exp(1))) ##i get the following error: ##Error in integrate(f, -Inf, log(p -

Hi, I am trying to fit a function of the form: y = A0 + A1 * exp( -0.5* ( (X - Mu1) / Sigma1 )^2 ) - A2 * exp ( -0.5* ( (X-Mu2)/Sigma2 )^2 ) i.e. a mean term (A0) + a difference between two gaussians. The constraints are A1,A2 >0, Sigma1,Sigma2>0, and usually Sigma2>Sigma1. The plot looks like a "Mexican Hat". I had trouble (poor fits) fitting this function to toy data