search for: theta_t

Hi, I am trying to figure how to use dlm with constant terms (possibly time-dependent) added to both equations y_t = c_t + F_t\theta_t + v_t \theta_t = d_t + G_t\theta_{t-1} + w_t, in the way that S-PLUS Finmetrics does? Is there any straightforward way to transform the above to the default setup? Thanks, Tsvetan -------------------------------------------------------- NOTICE: If received in error, please destroy and notify sen...

Dear all, I am currently trying to use the "dlm" package for Kalman filtering. My model is very simple: Y_t = F'_t Theta_t + v_t Theta_t = G_t Theta_t-1 + w_t v_t ~ N(0,V_t) = N(0,V) w_t ~ N(0,W_t) = N(0,W) Y_ t is a univariate time series (1x1) F_t is a vector of factor returns (Kx1) Theta_t is the state vector (Kx1) G_t is the identity matrix My first challenge is to get the Maximum Likelihood estima...

I am looking for a Kalman filter that can handle a control input. I thought that l.SS was suitable however, I can't get it to work, and wonder if I am not using the right function. What I want is a Kalman filter that accepts exogenous inputs where the input is found using the algebraic Ricatti equation solution to a penalty function. If K is the gain matrix then the exogenous input

...ched packages: [1] lme4_0.999375-26 Matrix_0.999375-11 lattice_0.17-13 loaded via a namespace (and not attached): [1] grid_2.7.2 > fm1 <- lmer(Reaction ~ Days + (Days|Subject), sleepstudy) > sm1 <- mcmcsamp(fm1, 5000) Error in .local(object, n, verbose, ...) : Code for non-trivial theta_T not yet written ## I cannot find exactly what this theta_T error means, although I do find it mentioned in what I believe to be source code. Regardless, I cannot understand why the mcmcsamp returns the error for this data set. Even when I change the model and the mcmcsamp appears to run, the out...

...factor models. When I started to read the functions on R, I got to the function ss on the library sspir. From what I understood this function is similar to SsfFit from S-PLUS. But for my models purpose there is something left to be desired. Its formulation follow these equations: *Y_t = F_t^T * theta_t + v_t, v_t ~ N(0,V_t)* *theta_t = G_t * theta_{t-1} + w_t, w_t ~ N(0,W_t)* Actually I wanted to add these two functions (-logA and a) Y(t) = -log(A(t))/tau + (B(t)/tau) * X(t) + Error (measurement equation) X(t) = a(t) + b(t) * X(t-1) + Error (Transition Equation) Have...

...value of a stock. Now suppose I want a trading strategy to be: x_t+1 = c(v_t – p_t) where c is a costant. I know, from the paper where this equations come from (Farmer and Joshi, The price dynamics of common trading strategies, 2001) that the induced price dynamics is: r_t+1 = –a*r_t + a*e_t + theta_t+1 and p_t+1 = p_t +r_t+1 where r_t = p_t – p_t-1 , e_t = v_t – v_t-1 and a = c/lambda (lambda is another constant). How can I simulate the equations I have just presented? I have good confidence with R for statistical analysis, but not for simulation therefore I apologize for my ignorance. What...

Dear R Users, I am new to state-space modeling. I am using SSPIR package for Kalman Filter. I have a data set containing one dependent variable and 7 independent variables with 250 data points. I want to use Kalman Filter for forecast the future values of the dependent variable using a multiple regression framework. I have used ssm function to produce the state space (SS)

...! Is anyone familiar in how arima with xreg as given estimate models? .. how is the model assumed? supposing I write : arima(y, xreg=U, order=c(3,0,2)) how is y_t calculated? (supposing U has 2 columns, with U[1] being first column and U[2] second column) is it y_t = theta_(t-1)y_t-1 + .... + theta_t-3 y_t-3 + intercept + U[1]_t + psi[1]_t-1 U[1]_t-1 + psi[1]_t-2 U[1]_t-2 + ....+ psi[2]U[2]_t-2 + e_t + phi_t-1 e_t-1 + phi_t-2 e_t-2 ?? e_t .. etc. are the white noise series of the model. the documentation is totally vague when it comes to xreg. I hope it is like above :) Would appreciate an...

Just out of curiosity, why might this be occuring: > class(x6) [1] "mcmc" > crosscorr.plot(x6) NULL # Replicable code example(lmer) x6 <- mcmcsamp(fm1, n=1000) crosscorr.plot(x6)

...stimate models? .. > how is the model assumed? > > supposing I write : > > arima(y, xreg=U, order=c(3,0,2)) > > how is y_t calculated? (supposing U has 2 columns, with U[1] being > first column and U[2] second column) > > is it > > y_t = theta_(t-1)y_t-1 + .... + theta_t-3 y_t-3 + intercept + U[1]_t + > psi[1]_t-1 U[1]_t-1 + psi[1]_t-2 U[1]_t-2 + ....+ psi[2]U[2]_t-2 + > e_t + phi_t-1 e_t-1 + phi_t-2 e_t-2 > > ?? > > e_t .. etc. are the white noise series of the model. > > the documentation is totally vague when it comes to xreg. I hope it...

I am having a problem with the package SSPIR. The code below illustrates it. I keep getting the message: "Error in y - f : non-conformable arrays." I tried to tweak the code below in many different ways, for example, substituting rbind for cbind, and sometimes I get a different error message, but I could not find a variation of this code that would work. Any help will be greatly