Cover Image

Semi-Parametric Inference for Doubly Stochastic Spatial Point Processes: An Approximate Penalized Poisson Likelihood Approach

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cheng, Si, Wakefield, Jon, Shojaie, Ali
Format:	Preprint
Published:	2023
Subjects:	Methodology Computation Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Penalized Empirical Likelihood for Doubly Robust Causal Inference under Contamination in High Dimensions
by: Lee, Byeonghee, et al.
Published: (2025)

Estimation of High-Dimensional Markov-Switching VAR Models with an Approximate EM Algorithm
by: Li, Xiudi, et al.
Published: (2022)

Principal component analysis balancing prediction and approximation accuracy for spatial data
by: Cheng, Si, et al.
Published: (2024)

Learning Directed Acyclic Graphs from Partial Orderings
by: Shojaie, Ali, et al.
Published: (2024)

Order Selection in Vector Autoregression by Mean Square Information Criterion
by: Hellstern, Michael, et al.
Published: (2025)

Doubly regularized generalized linear models for spatial observations with high-dimensional covariates
by: Sondhi, Arjun, et al.
Published: (2024)

Predictive Causal Inference via Spatio-Temporal Modeling and Penalized Empirical Likelihood
by: Lee, Byunghee, et al.
Published: (2025)

BARTSIMP: flexible spatial covariate modeling and prediction using Bayesian additive regression trees
by: Jiang, Alex Ziyu, et al.
Published: (2023)

Neural Likelihood Surfaces for Spatial Processes with Computationally Intensive or Intractable Likelihoods
by: Walchessen, Julia, et al.
Published: (2023)

Proximal Projection for Doubly Sparse Regularized Models
by: He, Jia Wei, et al.
Published: (2026)

Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference
by: Kelly, Ryan P., et al.
Published: (2023)

Bayesian Semi-Parametric Spatial Dispersed Count Model for Precipitation Analysis
by: Nadifar, Mahsa, et al.
Published: (2025)

Exact and Approximate MCMC for Doubly-intractable Probabilistic Graphical Models Leveraging the Underlying Independence Model
by: Chen, Yujie, et al.
Published: (2025)

Likelihood-Free Adaptive Bayesian Inference via Nonparametric Distribution Matching
by: Lu, Wenhui Sophia, et al.
Published: (2025)

Approximate Maximum Likelihood Inference for Acoustic Spatial Capture-Recapture with Unknown Identities, Using Monte Carlo Expectation Maximization
by: Wang, Yuheng, et al.
Published: (2024)

Spectral Differential Network Analysis for High-Dimensional Time Series
by: Hellstern, Michael, et al.
Published: (2024)

Integer Programming for Learning Directed Acyclic Graphs from Non-identifiable Gaussian Models
by: Xu, Tong, et al.
Published: (2024)

Dimension-reduced Reconstruction Map Learning for Parameter Estimation in Likelihood-Free Inference Problems
by: Zhang, Rui, et al.
Published: (2024)

Inference for Heterogeneous Graphical Models using Doubly High-Dimensional Linear-Mixed Models
by: Yue, Kun, et al.
Published: (2024)

Benchmark of Likelihood-Free Inference Methods based on Neural and Optimal Transport Approaches
by: Aka, Samira, et al.
Published: (2026)

Asymptotic Time-Uniform Inference for Parameters in Averaged Stochastic Approximation
by: Xie, Chuhan, et al.
Published: (2024)

Likelihood Based Inference in Fully and Partially Observed Exponential Family Graphical Models with Intractable Normalizing Constants
by: Chen, Yujie, et al.
Published: (2024)

Doubly-Regressing Approach for Subgroup Fairness
by: Kim, Kunwoong, et al.
Published: (2025)

A Likelihood-Free Approach to Goal-Oriented Bayesian Optimal Experimental Design
by: Chakraborty, Atlanta, et al.
Published: (2024)

Doubly Robust Inference in Causal Latent Factor Models
by: Abadie, Alberto, et al.
Published: (2024)

Block Empirical Likelihood Inference for Longitudinal Generalized Partially Linear Single-Index Models
by: Zhang, Tianni, et al.
Published: (2026)

Scalable Bayesian Inference for Generalized Linear Mixed Models via Stochastic Gradient MCMC
by: Berchuck, Samuel I., et al.
Published: (2024)

Efficient Bayesian Inference for Spatial Point Patterns Using the Palm Likelihood
by: Collins, Kevin M., et al.
Published: (2025)

Local Interference: Removing Interference Bias in Semi-Parametric Causal Models
by: O'Riordan, Michael, et al.
Published: (2025)

Accelerated Inference for Partially Observed Markov Processes using Automatic Differentiation
by: Tan, Kevin, et al.
Published: (2024)

Likelihood-Preserving Embeddings for Statistical Inference
by: Akdemir, Deniz
Published: (2025)

A Tutorial on Doubly Robust Learning for Causal Inference
by: Hlynsson, Hlynur Davíð
Published: (2024)

A Pathwise Coordinate Descent Algorithm for LASSO Penalized Quantile Regression
by: Kim, Sanghee, et al.
Published: (2025)

Penalized Likelihood Approach for the Four-parameter Kappa Distribution
by: Papukdee, Nipada, et al.
Published: (2024)

Poisson Hyperplane Processes with Rectified Linear Units
by: Ge, Shufei, et al.
Published: (2026)

Comparing Data Assimilation and Likelihood-Based Inference on Latent State Estimation in Agent-Based Models
by: Kolic, Blas, et al.
Published: (2025)

Forests for Differences: Robust Causal Inference Beyond Parametric DiD
by: Souto, Hugo Gobato, et al.
Published: (2025)

Simulation-based Inference for High-dimensional Data using Surjective Sequential Neural Likelihood Estimation
by: Dirmeier, Simon, et al.
Published: (2023)

A Doubly Robust Machine Learning Approach for Disentangling Treatment Effect Heterogeneity with Functional Outcomes
by: Salmaso, Filippo, et al.
Published: (2026)

Proximal Approximate Inference in State-Space Models
by: Abdulsamad, Hany, et al.
Published: (2025)