Selected article for: "covariance matrix and inverse hessian matrix"

Author: Spencer Woody; Mauricio Garcia Tec; Maytal Dahan; Kelly Gaither; Spencer Fox; Lauren Ancel Meyers; James G Scott
Title: Projections for first-wave COVID-19 deaths across the US using social-distancing measures derived from mobile phones
  • Document date: 2020_4_22
  • ID: 87lxnslh_30
    Snippet: The model is fit by a penalized nonlinear least-squares procedure, encouraging the parameters of each state's λ i (t) curve to be shrunk towards a common conditional mean, given social-distancing covariates. They interpret the result as a hierarchical Bayesian MAP estimate under an assumed prior, and use the inverse Hessian matrix at the MAP estimate as plug-in estimate of the posterior covariance matrix for the model parameters......
    Document: The model is fit by a penalized nonlinear least-squares procedure, encouraging the parameters of each state's λ i (t) curve to be shrunk towards a common conditional mean, given social-distancing covariates. They interpret the result as a hierarchical Bayesian MAP estimate under an assumed prior, and use the inverse Hessian matrix at the MAP estimate as plug-in estimate of the posterior covariance matrix for the model parameters.

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