Results 51 to 60 of about 13,851,275 (245)
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 +3 more
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Characterization of the asymptotic distribution of semiparametric M-estimators [PDF]
, 2010 This paper develops a concrete formula for the asymptotic distribution of two-step, possibly non-smooth semiparametric M-estimators under general misspecification.
Sokbae Lee +5 more
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JTAM (Jurnal Teori dan Aplikasi Matematika)Regression analysis is one of the statistical methods used to model the relationship between response variables and predictor variables. Semiparametric regression is a combination of parametric and nonparametric regression.
Tiani Wahyu Utami +2 more
doaj +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
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Endogeneity in semiparametric binary response models [PDF]
, 2003 This paper develops and implements semiparametric methods for estimating binary response (binary choice) models with continuous endogenous regressors. It extends existing results on semiparametric estimation in single index binary response models to the ...
Blundell, R., Powell, J.L.
core
International Journal for Re-Views in Empirical Economics, 2019 This paper aims to replicate the semiparametric Value-At-Risk model by Dias (2014) and to test its legitimacy. The study confirms the superiority of semiparametric estimation over classical methods such as mixture normal and Student-t approximations in ...
Jiahua Xu
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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 +3 more
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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
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A semiparametric factor model for electricity forward curve dynamics [PDF]
In this paper we introduce the dynamic semiparametric factor model (DSFM) for electricity forward curves. The biggest advantage of our approach is that it not only leads to smooth, seasonal forward curves extracted from exchange traded futures and ...
Weron, Rafal, Borak, Szymon
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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