Description Usage Arguments Details Value See Also Examples
View source: R/load.Hst.ls.2Zs.R
Insert an observation matrix into space-time covariates, but segregate based on missing values
1 | load.Hst.ls.2Zs(Z, Z.na, Hst.ls.Z, xwhich, rgr.lags = c(0))
|
Z |
Observation data. A τ x n numeric matrix. |
Z.na |
Missing data indicator. A τ x n boolean matrix. |
Hst.ls.Z |
Space-time covariates. A list of length τ, each element should be a numeric n x p_st matrix. |
xwhich |
Which column-pair of |
rgr.lags |
Temporal lagging of |
This function, along with load.Hst.ls.Z
, allows the user to convert a set of observations into covariates for another set of observations. Unlike load.Hst.ls.Z
, this function splits Z
based on the argument Z.na
. Values associated with FALSE
elements of Z.na
are placed into the first column of the specified column-pair of Hst.ls.Z
, Values associated with TRUE
elements of Z.na
are placed into the second column of the specified column-pair of Hst.ls.Z
(all other values in in the specified column-pair of Hst.ls.Z
are zeroed).
An unnamed list of length τ, each element will be a numeric n x p_st matrix.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 | ###### here's an itty-bitty example
tau <- 7
n <- 5
Z <- matrix(1, tau, n)
Z.na <- matrix(FALSE, tau, n)
Z.na[2:3, 4] <- TRUE
Z[Z.na] <- 2
Hst.ls <- list()
for(i in 1:tau) { Hst.ls[[i]] <- matrix(rnorm(n*4), nrow=n) }
load.Hst.ls.2Zs(Z, Z.na, Hst.ls.Z=Hst.ls, 1, 0)
########## insert into cols 3 and 4
load.Hst.ls.2Zs(Z, Z.na, Hst.ls.Z=Hst.ls, 2, 0)
|
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