Results 21 to 30 of about 15,261 (244)
Semiparametric transition models [PDF]
Econometric Reviews, 2021 A new semiparametric time series model is introduced – the semiparametric transition (SETR) model – that generalizes the threshold and smooth transition models by letting the transition function to be of an unknown form. Estimation is based on a combination of the (local) least squares estimations of the transition function and regression parameters ...
Cizek, Pavel, Koo, Chao Hui
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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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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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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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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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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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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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NONPARAMETRIC ESTIMATION OF SEMIPARAMETRIC TRANSFORMATION MODELS [PDF]
Econometric Theory, 2016 In this paper we develop a nonparametric estimation technique for semiparametric transformation models of the form:H(Y) =φ(Z) +X′β+UwhereH,φare unknown functions,βis an unknown finite-dimensional parameter vector and the variables (Y,Z) are endogenous.
Florens, Jean-Pierre, Sokullu, Senay
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A semiparametric model for cluster data
The Annals of Statistics, 2009 In the analysis of cluster data, the regression coefficients are frequently assumed to be the same across all clusters. This hampers the ability to study the varying impacts of factors on each cluster. In this paper, a semiparametric model is introduced to account for varying impacts of factors over clusters by using cluster-level covariates.
Zhang, Wenyang, Fan, Jianqing, Sun, Yan
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