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Distributed lag non-linear models. [PDF]
AbstractEnvironmental stressors often show effects that are delayed in time, requiring the use of statistical models that are flexible enough to describe the additional time dimension of the exposure–response relationship. Here we develop the family of distributed lag non‐linear models (DLNM), a modelling framework that can simultaneously represent non‐
Gasparrini A, Armstrong B, Kenward MG.
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Predicting alfalfa leaf area index by non-linear models and deep learning models [PDF]
Leaf area index (LAI) of alfalfa is a crucial indicator of its growth status and a predictor of yield. The LAI of alfalfa is influenced by environmental factors, and the limitations of non-linear models in integrating these factors affect the accuracy of
Songtao Yang +6 more
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Distributed Lag Linear and Non-Linear Models in R: The Package dlnm [PDF]
Distributed lag non-linear models (DLNMs) represent a modeling framework to flexibly describe associations showing potentially non-linear and delayed effects in time series data.
Antonio Gasparrini
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The dressing method as non linear superposition in sigma models
We apply the dressing method on the Non Linear Sigma Model (NLSM), which describes the propagation of strings on ℝ × S2, for an arbitrary seed. We obtain a formal solution of the corresponding auxiliary system, which is expressed in terms of the ...
Dimitrios Katsinis +2 more
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Probabilistic time series forecasting with deep non‐linear state space models
Probabilistic time series forecasting aims at estimating future probabilistic distributions based on given time series observations. It is a widespread challenge in various tasks, such as risk management and decision making.
Heming Du, Shouguo Du, Wen Li
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Predicting the growth curve of body weight in madura cattle [PDF]
The growth curve of livestock animals is important to evaluate the biological development managed with a farming management system. This study aimed to estimate the growth curve of body weight (BW) in Madura cattle (Bos indicus) kept at the breeding ...
Hartati HARTATI +1 more
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Genome‐based prediction of Bayesian linear and non‐linear regression models for ordinal data
Linear and non‐linear models used in applications of genomic selection (GS) can fit different types of responses (e.g., continuous, ordinal, binary). In recent years, several genomic‐enabled prediction models have been developed for predicting complex ...
Paulino Pérez‐Rodríguez +5 more
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Non-Linear Models in Economic and Social Research
The article shows differences of presented models from models used in exact science. It analyzes the reasons why for mathematic models of economic and social systems we cannot reach the quantitative correlation of modeling results with indicators of real
L. F. Petrov
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Non Abelian T-duality in Gauged Linear Sigma Models
Abelian T-duality in Gauged Linear Sigma Models (GLSM) forms the basis of the physical understanding of Mirror Symmetry as presented by Hori and Vafa.
Nana Cabo Bizet +3 more
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Evaluation of Non- linear Growth Curves Models for Native Slow-growing Khazak Chickens [PDF]
Native poultry is a valuable genetic source with high resistance against diseases providing an important subject for breeding programs. The non-linear mathematical modeling of the growth pattern may partly explain the relationship between requirements ...
Faraji Arough H +3 more
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