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Distributed lag non-linear models. [PDF]
Abstract Environmental 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.
Gasparrini A, Armstrong B, Kenward MG.
europepmc +5 more sources
Neighborhood Approximations for Non-Linear Voter Models [PDF]
Non-linear voter models assume that the opinion of an agent depends on the opinions of its neighbors in a non-linear manner. This allows for voting rules different from majority voting. While the linear voter model is known to reach consensus, non-linear
Frank Schweitzer, Laxmidhar Behera
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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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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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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 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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