similar to: ARMA(1,1) for panel data

Hello, I am interested in estimating this type of random effects panel: y_it = x'_it * beta + u_it + e_it u_it = rho * u_it-1 + d_it rho belongs to (-1, 1) where: u and e are independently normally zero-mean distributed. d is also independently normally zero-mean distributed. So, I want random effects for group i to be correlated in t, following an AR(1) process. Any idea of how

Hi everyone, I am interested in estimating this type of random effects panel: y_it = x'_it * beta + u_it + e_it u_it = rho * u_it-1 + d_it rho belongs to (-1, 1) where: u and e are independent and normally zero-mean distributed. d is also independently normally zero-mean distributed. So, I want random effects for group i to be correlated in t, following an AR(1) process. I am

Hey all - I am a newbie on mixed-effects models. I want to estimate the following model: Y_it = alpha_0t + alpha_1t*X_it + e_it alpha_0t = gamma_00 + u_0t alpha_1t = gamma_10 + gamma_11*W_it + u_1j Where Y is my outcome, X is my level-1 predictor, and W is my level 2 predictor. I am not sure if I am doing it right. Is this the correct specification of the formula? model = lmer(Y ~ X + X:Y + (

Dear r-helpers, I am working with plm package. I am trying to fit a fixed effects (or a 'within') model of the form y_it = a_i + b_i*t + e_it, i.e. a model with an individual-specific intercept and an individual- specific slope. Does plm support this directly? Thanks in advance! Otto Kassi

Hello, I am using {plm} to estimate panel models. I want to estimate a model that includes fixed effects for time and individual, but has a random individual effect for the coefficient on the independent variable. That is, I would like to estimate the model: Y_it = a_i + a_t + B_i * X_it + e_it Where i denotes individuals, t denotes time, X is my independent variable, and B (beta) is the

Hello, I want to solve a nonlinear 3SLS problem with "nlsystemfit()". The equations are of the form y_it = f_i(x,t,theta) The functions f_i(.) have to be formulated as R-functions. When invoking "nlsystemfit()" I get the error Error in deriv.formula(eqns[[i]], names(parmnames)) : Function 'f1' is not in the derivatives table

Dear R users, I wish to manually demean a panel over time and entities. I tried to code the Wansbeek and Kapteyn (1989) transformation (from Baltagi's book Ch. 9). As a benchmark I use both the pmodel.response() and model.matrix() functions in package plm and the results from using dummy variables. As far as I understood the transformation (Ch.3), Q%*%y (with y being the dependent variable)

Dear List, why does as.data.frame(cbind()) transform numeric variables to factors, once one of the other variablesused is a character vector? # x.1 <- rnorm(10) x.2 <- c(rep("Test",10)) Foo <- as.data.frame(cbind(x.1)) is.factor(Foo$x.1) Foo <- as.data.frame(cbind(x.1,x.2)) is.factor(Foo$x.1) # I assume there is a good reason for this, can somebody explain? Thanks. Best,

Hello Following some standard textbooks on ARMA(1,1)-GARCH(1,1) (e.g. Ruey Tsay's Analysis of Financial Time Series), I try to write an R program to estimate the key parameters of an ARMA(1,1)-GARCH(1,1) model for Intel's stock returns. For some random reason, I cannot decipher what is wrong with my R program. The R package fGarch already gives me the answer, but my customized function

Hi, i am working in the forecast of the daily price crude . The last prices of this data are the following: 100.60 101.47 100.20 100.06 98.68 101.28 101.05 102.13 101.70 98.27 101.00 100.50 100.03 102.23 102.68 103.32 102.67 102.23 102.14 101.25 101.11 99.90 98.53 96.76 96.12 96.54 96.30 95.92 95.92 93.45 93.71 96.42 93.99 93.76 95.24 95.63 95.95 95.83 95.65

Hello R-list-members, I'm trying to model ARMA(0,2) & GARCH(1,1) process using the code below, but according to my textbook, the estimated parameters are wrong. The MA-parameters should be negative. (I've got the same problem using garchFit()). Can anyone tell me what I'm doing wrong? And how can I calculate the hessian matrix? Many thanks, Desislava Kavrakova Code:

Hi all, I got the daily stock return data from 2005 - 2008, calculated from HF minute data. (Thanks to Jeff and Josh). Now, I set 05 - 07yr as the carlibration period for estimating the parameters of ARMA(1,1)-GARCH(1,1) model, aqnd leave 08 for backtesting. So I use the return data observations from 1:760 (yr 05-07) to estimate the volatility on 2nd-Jan-08 (the position 761), then use the

On Apr 8, 2012, at 4:20 AM, Bill Wendling wrote: > On Apr 4, 2012, at 9:32 PM, Paul J. Lucas wrote: > >> This all seems to work just fine. I can throw a C++ exception either in a C++ object's constructor or in an ordinary member function and the stack unwinds correctly (the object's destructors are called) and the exception is propagated back up the C++ code that called the

Hi, how can I change the plotting symbol for the groups in a trellis panel dotplot. My graph is similar to: library(trellis) dotplot(variety ~ yield | site, data = barley, groups = year, key = simpleKey(levels(barley$year), space = "right"), xlab = "Barley Yield (bushels/acre) ", aspect=0.5, layout = c(1,6), ylab=NULL) I'd like to

Hi, is there anyway to adjust how ggplot(facet=) displays the layout of panels? I have a dataset with many 25 groups and gplot(y,x,facet= .~group) displays all 25 y~x plots next to each other so overall the plot is too wide. if i do the same plot in lattice xyploy(y~x|group) the y~x plots are arranged nicely 5 in each row to overall the plots is a nice 5 by 5 rectangular grid. Is there any way

I'd like to fit an ARMA(1,1) model to some data (Federal Reserve Bank interest rates) that looks like: ... 30JUN2006, 5.05 03JUL2006, 5.25 04JUL2006, N &lt;---- here! 05JUL2006, 5.25 ... One problem is that holidays have that "N" for their data. As a test, I tried fitting ARMA(1,1) with and without the holidays deleted. In other words, I fit the above data

Dear R users, I need to fit an ARMA model. As far as I've seen, EACF (extended ACF) is not available in R. 1. Let's say I fit a series of ARMA models in a loop. Given the code/output included below, how do I pull 'Model' and 'Fit' (AIC) from each summary() so that I can combine them into an array/data frame to be sorted by AIC? 2. Apart from EACF, are you aware perhaps

Hello, I am running an ARMA model to run forecast for changes in S&P 500 prices. My ARMA calculations look as follows armacal <- arma( spdata, order = c(0,4), lag = list(ma = c(1,2,4)) ) Output: Call: arma(x = spdata, order = c(0, 4), lag = list(ma = c(1, 2, 4)) ) Coefficient(s): ma1 ma2 ma4 intercept -0.073868 0.058020 -0.081292 0.007082 All's

Dear R experts, I am trying to estimate an ARMA 2,2 model with garch errors. I used the following code on R 2.9. #library library(fGarch) #data data1<-ts(read.table("C:/Users/falcon/Desktop/Time Series/exports/goods1.csv"), start=c(1992,1), frequency=12) head(data1) #garch garchFit(formula.mean= ~arma(2,2),formula.var=~garch(1,1), data=data1) but get this error: >

Hello,Could somebody tell me what is the difference between  theese 3 calls of functionsarma(x,order=c(1,0)), arima(x,order=c(1,0,0)) ar(x,order=1)?I expected same residuals of theese three models,but unexpectably for the first two R requiredinitial value of something (what?)...Thanks in advance!  [[alternative HTML version deleted]]