Results 51 to 60 of about 6,656,167 (244)

Investigating the validity of the gibrat law at the provincial level in Türkiye: parametric and semiparametric panel data models

Trakya Üniversitesi İktisadi ve İdari Bilimler Fakültesi E-Dergi
The growth of cities is closely linked to the overall economic growth of nations. Especially in urban planning, predicting and modelling the growth trajectory of cities is crucial for ensuring sustainable economic growth.
Şaban Kızılarslan, Mustafa Zuhal
doaj   +1 more source

A General Nonlinear Multilevel Structural Equation Mixture Model

Frontiers in Psychology, 2014
In the past 2 decades latent variable modeling has become a standard tool in the social sciences. In the same time period, traditional linear structural equation models have been extended to include nonlinear interaction and quadratic effects (e.g ...
Augustin eKelava, Holger eBrandt
doaj   +1 more source

Joint Analysis for Multivariate Longitudinal and Event Time Data With a Change Point Anchored at Interval‐Censored Event Time [PDF]

Stat Med
ABSTRACT Huntington's disease (HD) is an autosomal dominant neurodegenerative disorder characterized by motor dysfunction, psychiatric disturbances, and cognitive decline. The onset of HD is marked by severe motor impairment, which may be predicted by prior cognitive decline and, in turn, exacerbate cognitive deficits. Clinical data, however, are often
Zhan Y, Zheng C, Zhang Y.
europepmc   +2 more sources

Generalized Semiparametrically Structured Ordinal Models [PDF]

Biometrics, 2003
SummarySemiparametrically structured models are defined as a class of models for which the predictors may contain parametric parts, additive parts of covariates with an unspecified functional form, and interactions which are described as varying coefficients.
openaire   +3 more sources

Efficient estimation in semiparametric GARCH models [PDF]

Journal of Econometrics, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Drost, F.C., Klaassen, C.A.J.
openaire   +9 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

Learning sparse mixture‐of‐experts generalized linear models in ultrahigh dimensions

Canadian Journal of Statistics, EarlyView.
Abstract Motivated by the challenges of heterogeneity and high dimensionality in the analysis of modern data, we investigate continuous regularization methods for learning sparse mixture‐of‐experts generalized linear models (MoE‐GLM). Although there are foundational results about regularized estimators in a broad class of regression models including ...
Pengqi Liu, Abbas Khalili
wiley   +1 more source

Forecasting Duration in High‐Frequency Financial Data Using a Self‐Exciting Flexible Residual Point Process

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents a method for forecasting limit order book durations using a self‐exciting flexible residual point process. High‐frequency events in modern exchanges exhibit heavy‐tailed interarrival times, posing a significant challenge for accurate prediction.
Kyungsub Lee
wiley   +1 more source

A More Accurate Estimation of Semiparametric Logistic Regression

Mathematics, 2021
Growing interest in genomics research has called for new semiparametric models based on kernel machine regression for modeling health outcomes. Models containing redundant predictors often show unsatisfactory prediction performance.
Xia Zheng, Yaohua Rong, Ling Liu, Weihu Cheng   +3 more
doaj   +1 more source

MARS‐Diff: Guarded Residual Diffusion for Leakage‐Disciplined Probabilistic Portfolio‐Loss Forecasting

Journal of Forecasting, EarlyView.
ABSTRACT This paper develops Masked Asset–Regime Scenario Diffusion (MARS‐Diff), a leakage‐disciplined framework for probabilistic forecasting of multiday portfolio losses. The framework combines a regularized heterogeneous autoregressive model with exogenous predictors (HAR‐X) as its anchor, a train‐only masked representation of a high‐dimensional ...
Çağlar Sözen, Mervenur Sözen
wiley   +1 more source