Description Usage Arguments Value Note Examples
BLUP(X, F, V, var, f, v)
calculates the Best Linear Unbiased Predictor (BLUP) of FDSLRM time series in time t_{n+d}.
1 |
X |
time series. |
F |
design matrix for fixed effects. |
V |
design matrix for random effects. |
var |
variance parameters. |
f |
values of functions forming the columns of design matrix F computed in time t_{n+d}. |
v |
values of functions forming the columns of design matrix V computed in time t_{n+d}. |
BLUP of X_{t_{n+d}}.
Ver.: 13-Mar-2019 18:00:08.
1 2 3 4 5 6 7 8 9 | ## EXAMPLE 1
dt <- data.frame(t = c(1:24), x = c(40.3, 40.7, 38.5, 37.9, 38.6, 41.1, 45.2, 45.7, 46.7, 46.5, 45.2, 45.1, 45.8, 46.3, 47.5, 48.5, 49.1, 51.7, 50.6, 48, 44.7, 41.2, 40, 40.3))
F <- makeF(dt$t, c(1/24))
V <- makeV(dt$t, c(1/8,1/6))
f <- c(1, cos(2 * pi * 32/24), sin(2 * pi * 32/24))
v <- c(cos(2 * pi * 32/8), sin(2 * pi * 32/8), cos(2 * pi * 32/6), sin(2 * pi * 32/6))
var_estim <- NE(dt$x, F, V)
blup <- BLUP(dt$x, F, V, var_estim, f, v)
blup
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