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Dear R users, suppose we have a random walk such as: v_t+1 = v_t + e_t+1 where e_t is a normal IID noise pocess with mean = m and standard deviation = sd and v_t is the fundamental 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...

...dlm package and I would be very happy if someone could give me a hint! I am using the dlm package to get estimates for an endogenous rate of capacity utilization over time. The general form of a state space model is (1) b_t = G * b_t-1 + w_t w_t ~ N(0,W) (2) y_t= A' * x_t + H' * b_t + v_t v_t ~ N(0,V) (Hamilton 1984: 372) The investment function I would like to use for estimating my endogenous capacity utilization rate looks like (3) g_t = x[1] + x[2]*(u_t-un_t) + x[3]*r + v_t where g_t is the investment rate, r_t is the profit rate, u_t is the actual utilization rate and un...

Dear R-users, I am trying to estimate a state space model of the form (1) b_t = G * b_t-1 + w_t w_t ~ N(0,W) (2) y_t= A' * x_t + H' * b_t + v_t v_t ~ N(0,V) (Hamilton 1984: 372) In particular my estimation in state space form looks like (3) a3_t = 1 * a3_t-1 + w_t w_t ~ N(0,W) (4) g_t = (a1, a2) * (1, P_t)' + u_t * a3_t + v_t v_t ~ N(0,V) where g_t is the investment rate, P_t are profits and u_t is the utilization rate...

I am trying to make the following Kalman filter equations work and therefore produce their graphs. v_t=y_t - a_t a_t+1=a_t+K_t*v_t F_t=P_t+sigma.squared.epsilon P_t+1=P_t*(1-K_t)+sigma.squared.eta K_t=P_t/F_t Given: a_1=0,P_1=10^7,sigma.squared.epsilon=15099, sigma.squared.eta=1469.1 I have attached my code,which of course doesnt work.It produces NAs for the Fs,Ks and the a. Can somebody tell me p...

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

...els. 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 anyon...

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 estimators o...

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)

...) > fit <- StructTS(Nile, type = "level") > fit$loglik [1] -367.5194 When computing the log-likelihood with other packages such as KFAS and FKF, the loglikelihood value is around -645. For the local level model, the likelihood is defined by -0.5*n*log(2*pi) - 0.5*sum(log(F_t) + v_t^2/sqrt(F_t)) (see for example Durbin and Koopman (2001, page 30). But in StructTS, the likelihood is computed like this: loglik <- -length(y) * res$value + length(y) * log(2 * pi), where the first part coincides with the last part of the definition, but the constant part has wrong sign and it...

Dear R-Helpers, I am looking for ways to assess quality of a predictor of variance of a random variable. Here a two related, but yet distinct, setups. 1. I observe y_t, t=1,...,T which is normally distributed with unknown variance v_t (note that the variance is time-dependent). I have two "predictors" for v_t, dubbed v1_t and v2_t, and I want to tell which predictor is better. Here better is to be defined, but intuitively it is thought to be analogous to R^2 of an ordinary regression. I was thinking along the lines of...

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 sender. S...

Hi, After updating to R-3.0 beta r62328, I get the following: > install.packages("Biobase", type="source", repos="http://george2/BBS/2.12/bioc") Error in do.call(op, list(v_c, v_t[[op]])) : could not find function "R (>=2.15.1)" The problem can be fixed by adding a space after >= in the offending package's DESCRIPTION file and re-generating the PACKAGES file with tools:::write_PACKAGES(). However, this worked OK in r62077. I'm not sure if >=2.1...

Dear all, First I apologize if my question is quite simple, but i'm very newbie with R. I have vectors of the form v = c(1,1,-1,-1,-1,1,1,1,1,-1,1) (longer than this one of course). The elements are only +1 or -1. I would like to calculate : - the frequencies of -1 occurences after 2 consecutives -1 - the frequencies of +1 occurences after 2 consecutives +1 It looks probably something like

Hello Mentors, I am currently finding bug in Local Function related optimization due to which runtime failures are observed in some test cases, as those test cases are containing very large function with recursion and object oriented code so I am not able to find a pattern which is causing failure. So I tried following simple case to understand expected behavior from this optimization. Consider

  Hello, fellow R users,   I recently need to estimate a dynamic linear model in the following form:   For the measurement equation:   Y_t = F_t * a_t + v_t   where Y_t is the observation. It is a 1 by q row vector for each t. F_t is my forecasting variable. It is a 1 by p row vector. a_t is my state variable. It is a p by q MATRIX of parameters with each column of the matrix being regression coefficient of a random variable in Y_t. And v is a multivar...

I have data that looks like this: > df1 group id 1 red A 2 red B 3 red C 4 blue D 5 blue E 6 blue F I want a list of the groups containing vectors with the ids. I am avoiding subset(), as it is only recommended for interactive use. Here's what I have so far: df1 <- data.frame(group=c("red", "red", "red", "blue",