Results 11 to 20 of about 6,937 (202)
A semiparametric model for vQTL mapping. [PDF]
Biometrics, 2017 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 C, Ning Y, Wei P, Cao Y, Chen Y.
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Adaptive Semiparametric Language Models [PDF]
Transactions of the Association for Computational Linguistics, 2021 AbstractWe present a language model that combines a large parametric neural network (i.e., a transformer) with a non-parametric episodic memory component in an integrated architecture. Our model uses extended short-term context by caching local hidden states—similar to transformer-XL—and global long-term memory by retrieving a set of nearest neighbor ...
Dani Yogatama +2 more
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Semiparametric Duration Models [PDF]
Journal of Business & 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
Drost, F.C., Werker, B.J.M.
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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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E-Jurnal Matematika, 2017 Semiparametric regression is a regression model that includes parametric components and nonparametric components in a model. The regression model in this research is truncated spline semiparametric regression with case studies of patients with Dengue ...
NI WAYAN MERRY NIRMALA YANI +2 more
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Investigation of Parametric, Non-Parametric and Semiparametric Methods in Regression Analysis
Sakarya Üniversitesi Fen Bilimleri Enstitüsü Dergisi, 2022 Regression analysis is known as statistical methods applied to model and analyze the relationship between variables. Regression method can be examined as parametric, non-parametric and semiparametric regression methods.The parametric regression method ...
Esra Yavuz, Mustafa Şahin
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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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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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