Objective digital data is scarce yet needed in many domains to enable
research that can transform the standard of healthcare. While data from
consumer-grade wearables and smartphones is more accessible, there is critical
need for similar data from clinical-grade devices used by patients with a
diagnosed condition. The prevalence of wearable medical devices in the diabetes
domain sets the stage for unique research and development within this field and
beyond. However, the scarcity of open-source datasets presents a major barrier
to progress. To facilitate broader research on diabetes-relevant problems and
accelerate development of robust computational solutions, we provide the
DiaTrend dataset. The DiaTrend dataset is composed of intensive longitudinal
data from wearable medical devices, including a total of 27,561 days of
continuous glucose monitor data and 8,220 days of insulin pump data from 54
patients with diabetes. This dataset is useful for developing novel analytic
solutions that can reduce the disease burden for people living with diabetes
and increase knowledge on chronic condition management in outpatient settings.

提供了 DiaTrend 数据集，该数据集是由 54 个糖尿病患者的连续血糖监测数据和胰岛素泵数据组成的整体数据，可用于开发新的分析解决方案，减少糖尿病患者的疾病负担并增加外科门诊管理慢性病的知识。

DiaTrend: 用于开发新型分析解决方案的先进糖尿病技术数据集

DiaTrend: A dataset from advanced diabetes technology to enable  development of novel analytic solutions

In this chapter, we will first present the most standard computational
challenges met in Bayesian Statistics, focussing primarily on mixture
estimation and on model choice issues, and then relate these problems with
computational solutions. Of course, this chapter is only a terse introduction
to the problems and solutions related to Bayesian computations. For more
complete references, see Robert and Casella (2004, 2009), or Marin and Robert
(2007), among others. We also restrain from providing an introduction to
Bayesian Statistics per se and for comprehensive coverage, address the reader
to Robert (2007), (again) among others.

介绍了贝叶斯统计中的混合估计和模型选择问题，以及与之相关的计算解决方案，参考文献主要为 Robert 和 Casella (2004, 2009) 和 Marin 和 Robert (2007) 等。