Trajectory inference and parameter estimation in stochastic models with temporally aggregated data
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DOI: 10.1007/s11222-017-9779-x
Abstract: Stochastic models are of fundamental importance in many scientific and engineering applications. For example, stochastic models provide valuable insights into the causes and consequences of intra-cellular fluctuations and inter-cellular heterogeneity in molecular biology. The chemical… read more here.
Keywords: temporally aggregated; estimation; aggregated data; model ... See more keywords
Logistic Regression Models for Aggregated Data
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DOI: 10.1080/10618600.2021.1895816
Abstract: Abstract Logistic regression models are a popular and effective method to predict the probability of categorical response data. However, inference for these models can become computationally prohibitive for large datasets. Here we adapt ideas from… read more here.
Keywords: models aggregated; regression models; logistic regression; aggregated data ... See more keywords
Extremal behaviour of aggregated data with an application to downscaling
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DOI: 10.1093/biomet/asy052
Abstract: &NA; The distribution of spatially aggregated data from a stochastic process X may exhibit tail behaviour different from that of its marginal distributions. For a large class of aggregating functionals ℓ we introduce the ℓ‐extremal… read more here.
Keywords: data application; behaviour aggregated; aggregated data; process ... See more keywords