This appendix illustrates the process of fitting various parameterisations of the SE1IjR model (M1j) to high-fidelity D1j incidence reports. We mean by parameterisation the decision of categorising mo

NIAID Data Ecosystem60

Mean parameter estimates, standard deviation (SD), Monte Carlo error (MC error), odds ratios (OR), and 95% credible intervals for best-fitting model investigating the effect of covariates on the probability of bovine tuberculosis infection from 2005–2010 in Modified Accredited Zone in Michigan, USA.

牛结核病风险因素分析

贝叶斯估计

“HET” represents the random effect capturing region-wide.

NIAID Data Ecosystem30

Identification and Bayesian Estimation of Dynamic Factor Models

动态因子模型

贝叶斯估计

We consider a set of minimal identification conditions for dynamic factor models. These conditions have economic interpretations and require fewer restrictions than the static factor framework. Under

DataCite Commons2024-03-24 更新90

Labour Force Survey Two-Quarter Longitudinal Dataset, April 2001 - June 2021: Secure Access

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纵向数据分析

<b>Background</b><br> The Labour Force Survey (LFS) is a unique source of information using international definitions of employment and unemployment and economic inactivity, together

DataCite Commons2025-11-11 更新60

Bayesian joint model parameter estimates for longitudinal and survival processes.

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