Results 11 to 20 of about 2,205,726 (308)
Distributed Lag Linear and Non-Linear Models in R: The Package dlnm [PDF]
Journal of Statistical Software, 2011 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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Distributed lag non-linear models. [PDF]
Stat Med, 2010 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.
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Neighborhood Approximations for Non-Linear Voter Models [PDF]
Entropy, 2015 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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Reducing and meta-analysing estimates from distributed lag non-linear models. [PDF]
BMC Med Res Methodol, 2013 BACKGROUND: The two-stage time series design represents a powerful analytical tool in environmental epidemiology. Recently, models for both stages have been extended with the development of distributed lag non-linear models (DLNMs), a methodology for ...
Gasparrini A, Armstrong B.
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Spatial Bayesian distributed lag non-linear models (SB-DLNM) for small-area exposure-lag-response epidemiological modelling. [PDF]
Int J EpidemiolQuijal-Zamorano M +3 more
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The dressing method as non linear superposition in sigma models
Journal of High Energy Physics, 2021 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
CAAI Transactions on Intelligence Technology, 2023 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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Non-Linear Models in Economic and Social Research
Вестник Российского экономического университета имени Г. В. Плеханова, 2022 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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Predicting the growth curve of body weight in madura cattle [PDF]
Kafkas Universitesi Veteriner Fakültesi Dergisi, 2021 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
The Plant Genome, 2020 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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