Cover Image

Prior- and likelihood-free probabilistic inference with finite-sample calibration guarantees

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cella, Leonardo, Hector, Emily C.
Format:	Preprint
Published:	2026
Subjects:	Methodology
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Divide-and-conquer with finite sample sizes: valid and efficient possibilistic inference
by: Hector, Emily C., et al.
Published: (2025)

In-sample calibration yields conformal calibration guarantees
by: Allen, Sam, et al.
Published: (2025)

Possibility-theoretic statistical inference offers performance and probativeness assurances
by: Cella, Leonardo, et al.
Published: (2023)

Pooling information in likelihood-free inference
by: Frazier, David T., et al.
Published: (2022)

Tail calibration of probabilistic forecasts
by: Allen, Sam, et al.
Published: (2024)

Misspecification-robust likelihood-free inference in high dimensions
by: Thomas, Owen, et al.
Published: (2020)

A likelihood-based Bayesian inference framework for the calibration of and selection between stochastic velocity-jump models
by: Ceccarelli, Arianna, et al.
Published: (2025)

Computationally efficient variational-like approximations of possibilistic inferential models
by: Cella, Leonardo, et al.
Published: (2024)

Composite likelihood inference for space-time point processes
by: Jalilian, Abdollah, et al.
Published: (2024)

Turning the information-sharing dial: efficient inference from different data sources
by: Hector, Emily C., et al.
Published: (2022)

Nonparametric inference with massive data via grouped empirical likelihood
by: Wang, Yongda, et al.
Published: (2025)

Composite likelihood inference for the Poisson log-normal model
by: Stoehr, Julien, et al.
Published: (2024)

Spectral domain likelihoods for Bayesian inference in time-varying parameter models
by: Gustafsson, Oskar, et al.
Published: (2024)

When the whole is greater than the sum of its parts: Scaling black-box inference to large data settings through divide-and-conquer
by: Hector, Emily C., et al.
Published: (2024)

Non-parametric inference on calibration of predicted risks
by: Sadatsafavi, Mohsen, et al.
Published: (2023)

Stabilised weighted data subsampling for accelerated inference in models with recursive likelihoods
by: Quiroz, Matias, et al.
Published: (2026)

Expectation-propagation for Bayesian empirical likelihood inference
by: Ng, Kenyon, et al.
Published: (2025)

Statistical inference of random graphs with a surrogate likelihood function
by: Wu, Dingbo, et al.
Published: (2022)

Re-examining and calibrating weighted survival analysis for causal inference
by: Xu, Wenfu, et al.
Published: (2026)

Semiparametric empirical likelihood inference for abundance from one-inflated capture-recapture data
by: Liu, Yang, et al.
Published: (2025)

Causal inference for calibrated scaling interventions on time-to-event processes
by: Rytgaard, Helene Charlotte Wiese, et al.
Published: (2025)

Approximating full conformal prediction: distribution free guarantees via the tournament correction
by: Bhattacharyya, Aabesh, et al.
Published: (2026)

LocalCop: An R package for local likelihood inference for conditional copulas
by: Acar, Elif F., et al.
Published: (2024)

Two-step semiparametric empirical likelihood inference from capture-recapture data with missing covariates
by: Liu, Yang, et al.
Published: (2025)

Marginal likelihoods for finite-support Huber contamination
by: Kim, Jaehoan
Published: (2026)

A calibrated BISG for inferring race from surname and geolocation
by: Greengard, Philip, et al.
Published: (2023)

Simplifying debiased inference via automatic differentiation and probabilistic programming
by: Luedtke, Alex
Published: (2024)

Doubly robust inference via calibration
by: van der Laan, Lars, et al.
Published: (2024)

Calibrated Bayesian inference for random fields on large irregular domains using the debiased spatial Whittle likelihood
by: Goodwin, Thomas, et al.
Published: (2025)

Simulation-calibration testing for inference in Lasso regressions
by: Pluntz, Matthieu, et al.
Published: (2024)

The arithmetic-harmonic inequality index: Theory, inference, and finite-sample analysis
by: Vila, Roberto, et al.
Published: (2026)

Maximum-likelihood estimation of the Matérn covariance structure of isotropic spatial random fields on finite, sampled grids
by: Simons, Frederik J., et al.
Published: (2025)

Prior distributions for Gaussian processes in computer model emulation and calibration
by: Gu, Mengyang, et al.
Published: (2025)

Feasible pairwise pseudo-likelihood inference on spatial regressions in irregular lattice grids: the KD-T PL algorithm
by: Arbia, Giuseppe, et al.
Published: (2024)

Survey calibration for causal inference: a simple method to balance covariate distributions
by: Beręsewicz, Maciej
Published: (2023)

A note on incorrect inferences in non-binary qualitative probabilistic networks
by: Carter, Jack Storror
Published: (2022)

Causal Regularization: On the trade-off between in-sample risk and out-of-sample risk guarantees
by: Kania, Lucas, et al.
Published: (2022)

Distribution-free inference with hierarchical data
by: Lee, Yonghoon, et al.
Published: (2023)

A family of toroidal diffusions with exact likelihood inference
by: García-Portugués, Eduardo, et al.
Published: (2024)

Redefining shared information: a heterogeneity-adaptive framework for meta-analysis
by: Davis, Elizabeth M., et al.
Published: (2026)