Results 11 to 20 of about 19,219 (292)
Semiparametric Duration Models [PDF]
Journal of Business and Economic Statistics, 2004 In this article we consider semiparametric duration models and efficient estimation of the parameters in a non-iid environment. In contrast to classical time series models where innovations are assumed to be iid we show that in, for example, the often-used autoregressive conditional duration (ACD) model, the assumption of independent innovations is too
Feike C Drost, Bas J M Werker
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Efficient Estimation in Semiparametric GARCH Models [PDF]
Journal of Econometrics, 1997 It is well-known that financial data sets exhibit conditional heteroskedasticity.GARCH type models are often used to model this phenomenon. Since the distribution of the rescaled innovations is generally far from a normal distribution, a semiparametric ...
Klaassen, C.A.J., Drost, F.C.
core +9 more sources
A Semiparametric Model for VQTL Mapping [PDF]
Biometrics, 2016 Summary Quantitative trait locus analysis has been used as an important tool to identify markers where the phenotype or quantitative trait is linked with the genotype. Most existing tests for single locus association with quantitative traits aim at the detection of the mean differences across genotypic groups.
Hong, Chuan +4 more
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A semiparametric conditional duration model [PDF]
Economics Letters, 2014 zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Dungey, Mardi +3 more
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Semiparametric hierarchical model with heteroscedasticity [PDF]
Statistics and Its Interface, 2017 Recent work on hierarchical data analysis mainly focuses on the multilevel structure of the mean response. Little research for hierarchical heteroscedasticity was done in the literature. In this paper, we propose a class of hierarchical models with heteroscedasticity and then investigate the semi-parametric statistical inferences.
Ma, Chuoxin, Tian, Maozai, Pan, Jianxin
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SEMIPARAMETRIC MULTIVARIATE VOLATILITY MODELS [PDF]
Econometric Theory, 2007 Summary: We consider a model for a multivariate time series where the conditional covariance matrix is a function of a finite-dimensional parameter and the innovation distribution is nonparametric. The semiparametric lower bound for the estimation of the Euclidean parameter is characterized, and it is shown that adaptive estimation without ...
Hafner, C.M., Rombouts, J.V.K.
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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
doaj +1 more source
Spline Semiparametric Regression Models
Journal of Kufa for Mathematics and Computer, 2015 In this paper, we study semiparametric regression models with spline smoothing, and determining the numbers of knots and their locations by using some statistical criteria, a simulation model has been performed.
Ameera Jaber Mohaisen +1 more
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Semiparametric modelling of multicategorical data [PDF]
Journal of Statistical Computation and Simulation, 2004 Parametric multicategorical models are an established tool in statistical data analysis. Alternative semi-parametric models are introduced where part of the explanatory variables is still linearly parametrized and the rest is given as a sum of unspecified functions of the explanatory variables.
Tutz, Gerhard, Scholz, T.
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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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