activity
20132021
most citedGranger Causality Networks for Categorical Time Series

11 citations · 42 across the 16 of their papers we have counts for

collaborators

26 papers

stat.ME20212 cited

Joint Estimation and Inference for Multi-Experiment Networks of High-Dimensional Point Processes

Xu Wang, Ali Shojaie

Modern high-dimensional point process data, especially those from neuroscience experiments, often involve observations from multiple conditions and/or experiments. Networks of inte…

stat.ME20211 cited

Direct estimation of differential Granger causality between two high-dimensional time series

Yue Wang, Jing Ma, Ali Shojaie

Differential Granger causality, that is understanding how Granger causal relations differ between two related time series, is of interest in many scientific applications. Modeling…

stat.ME2021

Interaction Models and Generalized Score Matching for Compositional Data

Shiqing Yu, Mathias Drton, Ali Shojaie

Applications such as the analysis of microbiome data have led to renewed interest in statistical methods for compositional data, i.e., multivariate data in the form of probability…

stat.ME20212 cited

Causal Structural Learning Via Local Graphs

Wenyu Chen, Mathias Drton, Ali Shojaie

We consider the problem of learning causal structures in sparse high-dimensional settings that may be subject to the presence of (potentially many) unmeasured confounders, as well…

cs.LG2021

Definite Non-Ancestral Relations and Structure Learning

Wenyu Chen, Mathias Drton, Ali Shojaie

In causal graphical models based on directed acyclic graphs (DAGs), directed paths represent causal pathways between the corresponding variables. The variable at the beginning of s…

stat.ME2021

Inference on function-valued parameters using a restricted score test

Aaron Hudson, Marco Carone, Ali Shojaie

It is often of interest to make inference on an unknown function that is a local parameter of the data-generating mechanism, such as a density or regression function. Such estimand…