25 citations · 37 across the 14 of their papers we have counts for
4 papers · 1 filter
General Covariance-Based Conditions for Central Limit Theorems with Dependent Triangular Arrays
Arun G. Chandrasekhar, Matthew O. Jackson, Tyler H. McCormick +1
We present a general central limit theorem with simple, easy-to-check covariance-based sufficient conditions for triangular arrays of random vectors when all variables could be int…
Identifying the latent space geometry of network models through analysis of curvature
Shane Lubold, Arun G. Chandrasekhar, Tyler H. McCormick
A common approach to modeling networks assigns each node to a position on a low-dimensional manifold where distance is inversely proportional to connection likelihood. More positiv…
Consistently estimating network statistics using Aggregated Relational Data
Emily Breza, Arun G. Chandrasekhar, Shane Lubold +2
Collecting complete network data is expensive, time-consuming, and often infeasible. Aggregated Relational Data (ARD), which capture information about a social network by asking a…
Using Aggregated Relational Data to feasibly identify network structure without network data
Emily Breza, Arun G. Chandrasekhar, Tyler H. McCormick +1
Social network data is often prohibitively expensive to collect, limiting empirical network research. Typical economic network mapping requires (1) enumerating a census, (2) elicit…