Results 41 to 50 of about 777 (154)

Hidden Markov graphical models with state‐dependent generalized hyperbolic distributions

Canadian Journal of Statistics, EarlyView.
Abstract In this article, we develop a novel hidden Markov graphical model to investigate time‐varying interconnectedness between different financial markets. To identify conditional correlation structures under varying market conditions and accommodate shape features embedded in financial time series, we rely upon the generalized hyperbolic family of ...
Beatrice Foroni, Luca Merlo, Lea Petrella   +2 more
wiley   +1 more source

Semiparametric Semivariogram Modeling with a Scaling Criterion for Node Spacing: A Case Study of Solar Radiation Distribution in Thailand

Mathematics, 2020
Geostatistical interpolation methods, sometimes referred to as kriging, have been proven effective and efficient for the estimation of target quantity at ungauged sites.
Sompop Moonchai, Nawinda Chutsagulprom
doaj   +1 more source

Dynamic survival risk prediction with time‐varying high‐dimensional images

Canadian Journal of Statistics, EarlyView.
Abstract Integrating longitudinal data with survival models is a prevalent strategy for dynamic survival risk prediction while accounting for subjects' longitudinally observed variables. However, existing methods primarily focus on scalar longitudinal data and seldom tackle the complexities associated with high‐dimensional longitudinal imaging data ...
Bingfan Liu, Haolun Shi, Shu Jiang, Liangliang Wang, Da Ma, Mirza Faisal Beg, Jiguo Cao, for the Alzheimer's Disease Neuroimaging Initiative   +7 more
wiley   +1 more source

Copula‐based joint modelling of emergency department visits with time‐varying dependence

Canadian Journal of Statistics, EarlyView.
Abstract Jointly modelling multiple correlated count time series is essential in health services research, where outcomes like emergency visits for mental health and substance use often evolve together. Ignoring these dependencies can obscure meaningful trends and limit the effectiveness of policy evaluation.
Guanjie Lyu, Cindy Feng, Lihui Liu
wiley   +1 more source

Nonparametric Econometrics: The np Package

Journal of Statistical Software, 2008
We describe the R np package via a series of applications that may be of interest to applied econometricians. The np package implements a variety of nonparametric and semiparametric kernel-based estimators that are popular among econometricians.
Tristen Hayfield, Jeffrey S. Racine
doaj  

Semiparametric conformal prediction

CoRR
Many risk-sensitive applications require well-calibrated prediction sets over multiple, potentially correlated target variables, for which the prediction algorithm may report correlated errors. In this work, we aim to construct the conformal prediction set accounting for the joint correlation structure of the vector-valued non-conformity scores ...
Ji Won Park, Robert Tibshirani, Kyunghyun Cho   +2 more
openaire   +2 more sources

Analyzing zero‐truncated recurrent event data by stratified regression with time‐varying coefficients

Canadian Journal of Statistics, EarlyView.
Abstract This article presents a strategy for conducting regression analysis of zero‐truncated recurrent event data. The research is partly motivated by a pediatric mental health care (PMHC) program based on administrative data. We are particularly interested in how the occurrence of an event depends on its past occurrences and the associated ...
Anqi A. Chen, X. Joan Hu, Rhonda J. Rosychuk, Leilei Zeng   +3 more
wiley   +1 more source

Risk Forecasting in Shipping Exchange‐Traded‐Fund (ETF) Markets

International Journal of Finance &Economics, EarlyView.
ABSTRACT This article examines the risk properties of freight‐derivative‐based exchange‐traded funds (ETFs), focusing on the Breakwave Dry Bulk Shipping ETF (BDRY), and evaluates the accuracy of Value‐at‐Risk (VaR) and Expected Shortfall (ES) forecasts across a range of econometric models.
Christos Katris, Manolis G. Kavussanos, Stergiani (Stella) A. Moysiadou   +2 more
wiley   +1 more source

Semi- and Nonparametric ARCH Processes

Journal of Probability and Statistics, 2011
ARCH/GARCH modelling has been successfully applied in empirical finance for many years. This paper surveys the semiparametric and nonparametric methods in univariate and multivariate ARCH/GARCH models.
Oliver B. Linton, Yang Yan
doaj   +1 more source

Mapping Causal Biology: Mendelian Randomization in the Era of Big Data

Med Research, EarlyView.
Mendelian randomization (MR) leverages genetic variants to mitigate confounding biases in causal inference. This review systematically maps MR's methodological evolution, highlights its expanding applications in epidemiology and drug target validation, and outlines future directions for overcoming current biases through dynamic, multi‐omics, and cross ...
Xuanlu Shen, Chunrun Qu, Zeyu Wang, Jinglin Zhou, Hongwei Liu, Yingjie Li, Bowei Liu, Hao Zhang, Nan Zhang, Jingwei Zhang, Quan Cheng   +10 more
wiley   +1 more source