全部搜尋項
[  buster  ] [  bullseye  ] [  bookworm  ] [  trixie  ] [  sid  ]
[ 原始碼： r-cran-surveillance  ]

套件：r-cran-surveillance（1.19.0-2）

r-cran-surveillance 的相關連結

Screenshot

Debian 的資源：

下載原始碼套件 r-cran-surveillance：

維護小組：

外部的資源：

相似套件：

GNU R package for the Modeling and Monitoring of Epidemic Phenomena

Statistical methods for the modeling and monitoring of time series of counts, proportions and categorical data, as well as for the modeling of continuous-time point processes of epidemic phenomena.

The monitoring methods focus on aberration detection in count data time series from public health surveillance of communicable diseases, but applications could just as well originate from environmetrics, reliability engineering, econometrics, or social sciences. The package implements many typical outbreak detection procedures such as the (improved) Farrington algorithm, or the negative binomial GLR-CUSUM method of Höhle and Paul (2008) <doi:10.1016/j.csda.2008.02.015>. A novel CUSUM approach combining logistic and multinomial logistic modeling is also included. The package contains several real-world data sets, the ability to simulate outbreak data, and to visualize the results of the monitoring in a temporal, spatial or spatio-temporal fashion. A recent overview of the available monitoring procedures is given by Salmon et al. (2016) <doi:10.18637/jss.v070.i10>.

For the retrospective analysis of epidemic spread, the package provides three endemic-epidemic modeling frameworks with tools for visualization, likelihood inference, and simulation. hhh4() estimates models for (multivariate) count time series following Paul and Held (2011) <doi:10.1002/sim.4177> and Meyer and Held (2014) <doi:10.1214/14-AOAS743>. twinSIR() models the susceptible-infectious-recovered (SIR) event history of a fixed population, e.g, epidemics across farms or networks, as a multivariate point process as proposed by Höhle (2009) <doi:10.1002/bimj.200900050>. twinstim() estimates self-exciting point process models for a spatio-temporal point pattern of infective events, e.g., time-stamped geo-referenced surveillance data, as proposed by Meyer et al. (2012) <doi:10.1111/j.1541-0420.2011.01684.x>. A recent overview of the implemented space-time modeling frameworks for epidemic phenomena is given by Meyer et al. (2017) <doi:10.18637/jss.v077.i11>.

標籤: 領域: 醫學, 實做語言: GNU R, 使用者介面: interface::commandline, role::program

其他與 r-cran-surveillance 有關的套件

  • 依賴
  • 推薦
  • 建議
  • 增強

下載 r-cran-surveillance

下載可用於所有硬體架構的
硬體架構 套件大小 安裝後大小 檔案
armhf 5，643。2 kB6，804。0 kB [檔案列表]