Results 21 to 30 of about 13,851,275 (245)
Model and Variable Selection Procedures for Semiparametric Time Series Regression
Journal of Probability and Statistics, 2009 Semiparametric regression models are very useful for time series analysis. They facilitate the detection of features resulting from external interventions.
Risa Kato, Takayuki Shiohama
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Semiparametric Regression in Capture–Recapture Modeling [PDF]
Biometrics, 2006 SummaryCapture–recapture models were developed to estimate survival using data arising from marking and monitoring wild animals over time. Variation in survival may be explained by incorporating relevant covariates. We propose nonparametric and semiparametric regression methods for estimating survival in capture–recapture models.
Gimenez, Olivier +4 more
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Semiparametric modeling of multiple quantiles
Journal of Econometrics, 2019 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Catania L., Luati A.
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Analysis of The Debtor's Endurance using Cox Regression Semiparametric Method
Jurnal Ilmu Keuangan dan Perbankan, 2022 The aim of this research was conducted to determine the factors that influence the resilience of car loan debtors in an area. The research method used is semiparametric Cox regression on secondary data, WAREHOUSE consisting of the customer profile ...
Vitri Aprilla Handayani* +3 more
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Discrete Dynamics in Nature and Society, 2019 This article aims to investigate the Value at Risk of basis for stock index futures hedging in China. Since the RS-GARCH model can effectively describe the state transition of variance in VaR and the two-state Markov process can significantly reduce the ...
Liang Wang +3 more
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A Semiparametric Sequential Ordinal Model with Applications to Analyse First Birth Intervals
Austrian Journal of Statistics, 2016 A semiparametric sequential ordinal model is proposed to analyze socio-demographic and spatial determinants of first birth intervals after marriage. Random effects are introduced to capture spatially structured and unstructured latent covariates.
Lawrence Kazembe
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Semiparametric Integrated and Additive Spatio-Temporal Single-Index Models
Mathematics, 2023 In this paper, we introduce two semiparametric single-index models for spatially and temporally correlated data. Our first model has spatially and temporally correlated random effects that are additive to the nonparametric function, which we refer to as ...
Hamdy F. F. Mahmoud, Inyoung Kim
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Semiparametric Bayesian inference in multiple equation models [PDF]
, 2005 This paper outlines an approach to Bayesian semiparametric regression in multiple equation models which can be used to carry out inference in seemingly unrelated regressions or simultaneous equations models with nonparametric components.
Poirier, Dale J. +2 more
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A Semiparametric Multilevel Survival Model
Journal of the Royal Statistical Society Series C: Applied Statistics, 2004 SummaryWe propose a semiparametric multilevel survival model for clustered duration data in which the effect of a continuous covariate is represented by an unspecified, possibly non-linear, function. This model makes no distributional assumption about the cluster level random effects.
Zhang, Wenyang, Steele, Fiona
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Fast Algorithm for Impact Point Selection in Semiparametric Functional Models
Proceedings, 2019 A new sparse semiparametric functional model is proposed, which tries to incorporate the influence of two functional variables in a scalar response in a quite simple and interpretable way. One of the functional variables is included trough a single-index
Silvia Novo +2 more
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