| Library: | times |
| See also: | kfilter ksmoother kem |
| Quantlet: | kemitor | |
| Description: | Calculates observations of a given state-space model. The state-space model is assumed to be in the following form: y_t = H x_t + ErrY_t x_t = F x_t-1 + ErrX_t x_0 = mu |
| Usage: | y = kemitor(T,mu,H,F,ErrY,ErrX) | |
| Input: | ||
| T | number of observations to be generated | |
| mu | n x 1 vector (starting point of the model) | |
| H | m x n matrix | |
| F | n x n matrix | |
| ErrY | T x m matrix of errors | |
| ErrX | T x n matrix of errors | |
| Output: | ||
| y | T x m matrix of generated time series, T is the number of generated observations, m is the dimension of generated time series | |
library("xplore")
library("plot")
library("times")
randomize(0)
T = 100
mu = 10
H = 1
F = 1
ErrY = normal(T) .* 3
ErrX = normal(T) .* 3
rw = kemitor(T,mu,H,F,ErrY,ErrX)
rw = vec(1:T)~rw
rw = setmask(rw,"line", "blue", "thin")
disp = createdisplay(1,1)
show(disp,1,1,rw)
Generates a random walk with errors.
library("xplore")
library("plot")
library("times")
randomize(0)
T = 100
ErrX = normal(T)~(vec(1:T).*0)
ErrY = normal(T).*2
H = 1~0
F = #(0.5,1)~#(-0.3,0)
x0 = #(0,0)
ar2 = kemitor(T,x0,H,F,ErrY,ErrX)
ar2 = vec(1:T)~ar2
ar2 = setmask(ar2,"line", "blue", "thin")
disp = createdisplay(1,1)
show(disp,1,1,ar2)
Generates an AR(2) with additive gaussian errors.
library("xplore")
library("plot")
library("times")
randomize(0)
T = 100
mu = #(20,0)
H = #(0.3,-0.3)~#(1,1)
F = #(1,0)~#(1,0)
ErrY =(normal(T) .* 3)~(normal(T) .* 3)
ErrX =(normal(T) .* 0)~(normal(T) .* 3)
ser = kemitor(T,mu,H,F,ErrY,ErrX)
ser = vec(1:T)~ser
ser1 = ser[,1]~ser[,2]
ser2 = ser[,1]~ser[,3]
ser1 = setmask(ser1,"line", "blue", "thin")
ser2 = setmask(ser2,"line", "blue", "thin")
disp = createdisplay(2,1)
show(disp,1,1,ser1)
show(disp,2,1,ser2)
Generates 100 observations of a given state space model.