Imagen de Portada

Adaptive Student's t-distribution with method of moments moving estimator for nonstationary time series

Fuente: arXiv

Guardado en:

Detalles Bibliográficos
Autor principal:	Duda, Jarek
Formato:	Preprint
Publicado:	2023
Materias:	Methodology Machine Learning Econometrics
Acceso en línea:	Acceder al recurso
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

Adaptive stable distribution and Hurst exponent by method of moments moving estimator for nonstationary time series
por: Duda, Jarek
Publicado: (2025)

Identification and estimation for matrix time series CP-factor models
por: Chang, Jinyuan, et al.
Publicado: (2024)

The Bayesian Context Trees State Space Model for time series modelling and forecasting
por: Papageorgiou, Ioannis, et al.
Publicado: (2023)

Inference for Batched Adaptive Experiments
por: Kemper, Jan, et al.
Publicado: (2025)

Adaptive Principal Component Regression with Applications to Panel Data
por: Agarwal, Anish, et al.
Publicado: (2023)

Adaptive, Rate-Optimal Hypothesis Testing in Nonparametric IV Models
por: Breunig, Christoph, et al.
Publicado: (2020)

Adaptive Estimation and Uniform Confidence Bands for Nonparametric Structural Functions and Elasticities
por: Chen, Xiaohong, et al.
Publicado: (2021)

Active Adaptive Experimental Design for Treatment Effect Estimation with Covariate Choices
por: Kato, Masahiro, et al.
Publicado: (2024)

Off-Policy Evaluation via Adaptive Weighting with Data from Contextual Bandits
por: Zhan, Ruohan, et al.
Publicado: (2021)

A step towards the integration of machine learning and classic model-based survey methods
por: Żądło, Tomasz, et al.
Publicado: (2024)

Machine Learning Who to Nudge: Causal vs Predictive Targeting in a Field Experiment on Student Financial Aid Renewal
por: Athey, Susan, et al.
Publicado: (2023)

Dynamic covariate balancing: estimating treatment effects over time with potential local projections
por: Viviano, Davide, et al.
Publicado: (2021)

Robustly estimating heterogeneity in factorial data using Rashomon Partitions
por: Venkateswaran, Aparajithan, et al.
Publicado: (2024)

A note on simulation methods for the Dirichlet-Laplace prior
por: Gruber, Luis, et al.
Publicado: (2025)

Batch-Adaptive Causal Annotations
por: Nwankwo, Ezinne, et al.
Publicado: (2025)

Optimal Conditional Inference in Adaptive Experiments
por: Chen, Jiafeng, et al.
Publicado: (2023)

Adaptive Experimental Design for Policy Learning
por: Kato, Masahiro, et al.
Publicado: (2024)

Demistifying Inference after Adaptive Experiments
por: Bibaut, Aurélien, et al.
Publicado: (2024)

Tackling Interference Induced by Data Training Loops in A/B Tests: A Weighted Training Approach
por: Si, Nian
Publicado: (2023)

Synthetic Combinations: A Causal Inference Framework for Combinatorial Interventions
por: Agarwal, Abhineet, et al.
Publicado: (2023)

Double Debiased Covariate Shift Adaptation Robust to Density-Ratio Estimation
por: Kato, Masahiro, et al.
Publicado: (2023)

STEEL: Singularity-aware Reinforcement Learning
por: Chen, Xiaohong, et al.
Publicado: (2023)

Individualized Policy Evaluation and Learning under Clustered Network Interference
por: Zhang, Yi, et al.
Publicado: (2023)

Estimating the Value of Evidence-Based Decision Making
por: Abadie, Alberto, et al.
Publicado: (2023)

Asymptotically Unbiased Synthetic Control Methods by Moment Matching
por: Kato, Masahiro, et al.
Publicado: (2023)

Augmented balancing weights as linear regression
por: Bruns-Smith, David, et al.
Publicado: (2023)

Educational Effects in Mathematics: Conditional Average Treatment Effect depending on the Number of Treatments
por: Nagai, Tomoko, et al.
Publicado: (2024)

Formalising causal inference as prediction on a target population
por: Höltgen, Benedikt, et al.
Publicado: (2024)

Functional effects models: Accounting for preference heterogeneity in panel data with machine learning
por: Salvadé, Nicolas, et al.
Publicado: (2025)

Vector Copula Variational Inference and Dependent Block Posterior Approximations
por: Fu, Yu, et al.
Publicado: (2025)

Robust Matrix Estimation with Side Information
por: Agarwal, Anish, et al.
Publicado: (2026)

Fast Online Changepoint Detection
por: Ghezzi, Fabrizio, et al.
Publicado: (2024)

Regularizing Extrapolation in Causal Inference
por: Arbour, David, et al.
Publicado: (2025)

Estimation of Optimal Dynamic Treatment Assignment Rules under Policy Constraints
por: Sakaguchi, Shosei
Publicado: (2021)

Machine-Learning-Assisted Comparison of Regression Functions
por: Yan, Jian, et al.
Publicado: (2025)

An Introduction to Double/Debiased Machine Learning
por: Ahrens, Achim, et al.
Publicado: (2025)

Partial Identification under Missing Data Using Weak Shadow Variables from Pretrained Models
por: Chen, Hongyu, et al.
Publicado: (2026)

Linear Multidimensional Regression with Interactive Fixed-Effects
por: Freeman, Hugo
Publicado: (2022)

xtdml: Double Machine Learning Estimation to Static Panel Data Models with Fixed Effects in R
por: Polselli, Annalivia
Publicado: (2025)

HMM-LSTM Fusion Model for Economic Forecasting
por: Sivakumar, Guhan
Publicado: (2025)