Parameter identifiability and model selection for sigmoid population growth models
Sigmoid growth models, such as the logistic, Gompertz and Richards’ models, are widely used to study population dynamics ranging from microscopic populations of cancer cells, to continental-scale human populations. Fundamental questions about model selection and parameter estimation are critical if...
Asıl Yazarlar: | Simpson, MJ, Browning, AP, Warne, DJ, Maclaren, OJ, Baker, RE |
---|---|
Materyal Türü: | Journal article |
Dil: | English |
Baskı/Yayın Bilgisi: |
Elsevier
2021
|
Benzer Materyaller
-
Identifiability analysis for stochastic differential equation models in systems biology
Yazar:: Browning, AP, ve diğerleri
Baskı/Yayın Bilgisi: (2020) -
Practical parameter identifiability for spatio-temporal models of cell invasion
Yazar:: Simpson, MJ, ve diğerleri
Baskı/Yayın Bilgisi: (2020) -
Profile likelihood analysis for a stochastic model of diffusion in heterogeneous media
Yazar:: Simpson, MJ, ve diğerleri
Baskı/Yayın Bilgisi: (2021) -
Rapid Bayesian inference for expensive stochastic models
Yazar:: Warne, DJ, ve diğerleri
Baskı/Yayın Bilgisi: (2021) -
Reliable and efficient parameter estimation using approximate continuum limit descriptions of stochastic models
Yazar:: Simpson, MJ, ve diğerleri
Baskı/Yayın Bilgisi: (2022)