kalmanBucyFilter {yuima} | R Documentation |
Kalman-Bucy Filter
Description
Estimates values of unobserved variables from observed variables in a Linear State Space Model.
Usage
kalmanBucyFilter(
yuima, params, mean_init, vcov_init = NULL, delta.vcov.solve = 0.001,
are = FALSE, explicit = FALSE, time_homogeneous = FALSE,
env = globalenv()
)
Arguments
yuima |
A |
params |
A list of numeric values specifying the names and values of the model parameters. |
mean_init |
A numeric value specifying the initial value of the unobserved variables. |
vcov_init |
A matrix specifying the initial variance-covariance of the unobserved variables.
This argument is required if |
delta.vcov.solve |
A numeric value specifying the step size used to solve the mean squared error of the estimator. |
are |
A logical value. If |
explicit |
A logical value. If |
time_homogeneous |
A logical value. If |
env |
An environment object specifying the environment in which the model coefficients are evaluated. |
Value
A yuima.kalmanBucyFilter
object.
model |
A |
mean |
A |
vcov |
An array object containing the estimated mean squared error of the estimator of unobserved variables. |
mean.init |
A numeric value representing the initial value of unobserved variables. |
vcov.init |
A matrix representing the initial mean squared error of the estimator of unobserved variables. |
delta |
A numeric value representing the time step of observations. |
data |
A |
Author(s)
YUIMA TEAM
References
Liptser, R. S., & Shiryaev, A. N. (2001). Statistics of Random Processes: General Theory. Springer.
Examples
vcov_init <- matrix(0.1)
mean_init <- 0
a <- 1.5
b <- 0.3
c <- 1
sigma <- 0.02
n <- 10^4
h <- 0.001
trueparam <- list(a = a, b = b, c = c, sigma = sigma)
mod <- setModel(drift = c("-a*X", "c*X"),
diffusion = matrix(c("b", "0", "0", "sigma"), 2, 2),
solve.variable = c("X", "Y"), state.variable = c("X", "Y"),
observed.variable = "Y")
samp <- setSampling(delta = h, n = n)
yuima <- simulate(mod, sampling = samp, true.parameter = trueparam)
res <- kalmanBucyFilter(
yuima, trueparam, mean_init, vcov_init, 0.001,
are = FALSE, env = globalenv()
)
# vcov and mean slots are accesible by mean and vcov method
mean(res)
vcov(res)