Description Usage Arguments Value Examples
In our time lagged regression problem, each covariate x_i is either present or absent for all lags, this function makes it easy to only specify the general sparsity, and convert it for all 5 lags. Used for both generation of response, and for the estimation purpose. Caution: so far only for total of 10 covariates!
1 | full.index(xs)
|
xs |
a vector. Index of non 0 covariates |
a list of components
xs |
The initial indices, also lag0 (at t-0) |
in2 |
Indices for lag1, t-1 |
in3 |
Indices for lag2, t-2 |
in4 |
Indices for lag3, t-3 |
in5 |
Indices for lag4, t-4 |
1 2 | xs.est <- c(4, 5, 6, 7, 8, 9, 10)
fullindex = full.index(xs.est)
|
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