Results 1 to 10 of about 6,886 (164)
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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ESTIMASI PARAMETER COX SEMIPARAMETRIC HAZARDS MODEL DENGAN METODE EFRON PADA DATA TERSENSOR KANAN
Jurnal Matematika UNAND, 2021 Salah satu kendala yang sering dihadapi pada penelitian survival adalah adanya data tersensor. Jika data tersensor dihilangkan, maka akan terjadi bias. Pengolahan data tersensor dapat dilakukan dengan Cox Semiparametric Hazards model. Pada penelitian ini,
TEDY MACHMUD +3 more
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THE APPLICATION OF THE SEMIPARAMETRIC GSTAR MODEL IN DETERMINING GAMMA-RAY LOG DATA ON SOIL LAYERS
Media Statistika, 2022 This research examines the semiparametric Generalized Space-Time Autoregressive (GSTAR) spacetime modeling and determines its spatial weight. In general, the spatial weights used are uniform, binary weights, and based on the distance, the result is a ...
Yundari Yundari, Shantika Martha
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SMALL AREA ESTIMATION OF MEAN YEARS SCHOOL IN KABUPATEN BOGOR USING SEMIPARAMETRIC P-SPLINE
Barekeng, 2022 The Fay-Herriot model, generally uses the EBLUP (Empirical Best Linear Unbiased Prediction) method, is less flexible due to the assumption of linearity.
Christiana Anggraeni Putri +2 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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A Semiparametric Tilt Optimality Model
Stats, 2022 Practitioners often face the situation of comparing any set of k distributions, which may follow neither normality nor equality of variances. We propose a semiparametric model to compare those distributions using an exponential tilt method.
Chathurangi H. Pathiravasan +1 more
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Right-Censored Time Series Modeling by Modified Semi-Parametric A-Spline Estimator
Entropy, 2021 This paper focuses on the adaptive spline (A-spline) fitting of the semiparametric regression model to time series data with right-censored observations.
Dursun Aydın +2 more
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