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1. Bayesian Sequential Inference for Dynamic Regression Models
Sammanfattning : Many processes evolve over time and statistical models need to be adaptive to change. This thesis proposes flexible models and statistical methods for inference about a data generating process that varies over time. The models considered are quite general dynamic predictive models with parameters linked to a set of covariates via link functions. LÄS MER
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