peer.avg: Computing peer average value

In PartialNetwork: Estimating Peer Effects Using Partial Network Data

Computing peer average value

Description

peer.avg computes peer average value using network data (as a list) and observable characteristics.

Usage

peer.avg(Glist, V, export.as.list = FALSE)

Arguments

Glist	the adjacency matrix or list sub-adjacency matrix.
V	vector or matrix of observable characteristics.
export.as.list	(optional) boolean to indicate if the output should be a list of matrices or a single matrix.

Value

the matrix product diag(Glist[[1]], Glist[[2]], ...) %*% V, where diag() is the block diagonal operator.

See Also

sim.network

Examples

# Generate a list of adjacency matrices
## sub-network size
N  <- c(250, 370, 120)  
## rate of friendship
p  <- c(.2, .15, .18)   
## network data
u  <- unlist(lapply(1: 3, function(x) rbinom(N[x]*(N[x] - 1), 1, p[x])))
G  <- vec.to.mat(u, N, normalise = TRUE)

# Generate a vector y
y  <- rnorm(sum(N))

# Compute G%*%y
Gy <- peer.avg(Glist = G, V = y)

PartialNetwork documentation built on May 29, 2024, 10:08 a.m.