This matrix demonstrates an internal data structure of how `tmlenet`

stores the input network.
The network in this matrix is derived from the column `"Net_str"`

of the dataset `df_netKmax6`

.
Both, this matrix and the vector of strings in column `"Net_str"`

, represent the same network and both can be used
for specifying the input network to `tmlenet`

function.
The network matrix may be specified by using the argument `NETIDmat`

of the `tmlenet`

function.
Inputing the network via this type of a matrix may lead to significant reduction in total run time,
since any network specified as a vector of strings, such as in column "Net_str",
will be first converted to this type of matrix representation.

1 |

See below and Example 3 in `tmlenet`

help file for examples constructing this matrix from the initial network input in
column `"Net_str"`

of `df_netKmax6`

.

This matrix consists of `1000`

rows and `6`

columns. Each row `i`

encodes a vector of network IDs of observation `i`

in
`df_netKmax6`

, i.e.,
`NetInd_mat_Kmax6[,i]`

contains a vector of observation row numbers in `df_netKmax6`

that are presumed "connected to" (or "friends of")
observation `i`

. Each observation can have at most 6 friends and if an observation `i`

has fewer than 6 friends the remainder row
of `NetInd_mat_Kmax6[,i]`

is filled with `NA`

s.

1 2 3 4 5 6 | ```
data(df_netKmax6)
Net_str <- df_netKmax6[, "Net_str"]
IDs_str <- df_netKmax6[, "IDs"]
net_ind_obj <- simcausal::NetIndClass$new(nobs = nrow(df_netKmax6), Kmax = ncol(df_netKmax6))
net_ind_obj$makeNetInd.fromIDs(Net_str = Net_str, IDs_str = IDs_str, sep = ' ')
NetInd_mat <- net_ind_obj$NetInd
``` |

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