Results 1 to 10 of about 6,447 (164)
Adaptive Semiparametric Language Models [PDF]
Transactions of the Association for Computational Linguistics, 2021 We 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.
Dani Yogatama +2 more
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Determining factors associated with the number of oocytes with appropriate morphology in infertile women: A cross-sectional study [PDF]
International Journal of Reproductive BioMedicineBackground: Infertility affects millions of couples worldwide. The number of morphologically normal oocytes (MNO) is a key determinant of assisted reproductive technology success. Accurate identification of influencing factors is limited by excess zeros
Zahra Asadollahi +6 more
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Combining semiparametric and machine learning approaches for short-term prediction of satellite clock bias [PDF]
Scientific ReportsAccurate modeling of satellite clock bias (SCB) is critical for enhancing high-precision positioning capabilities. Existing approaches, such as semiparametric adjustment models and neural networks, address the nonlinearity and non-stationarity of SCB ...
Lihong Jin +5 more
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Remote Sensing, 2021 Airborne laser scanning (ALS) acquisitions provide piecemeal coverage across the western US, as collections are organized by local managers of individual project areas.
Francisco Mauro +7 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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Semiparametric Additive Beta Regression Models
Revstat Statistical Journal, 2021 In this paper, we study a semiparametric additive beta regression model using a parameterization based on the mean and a dispersion parameter. This model is useful for situations where the response variable is continuous and restricted to the unit ...
Germán Ibacache-Pulgar +2 more
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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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REGION, 2022 This article introduces a new R package (pspatreg) for the estimation of semiparametric spatial autoregressive models. pspatreg fits penalized spline semiparametric spatial autoregressive models via Restricted Maximum Likelihood or Maximum Likelihood ...
Román Mínguez +2 more
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