Showing 4 of total 4 results (show query)
epinowcast
epinowcast:Flexible Hierarchical Nowcasting
Tools to enable flexible and efficient hierarchical nowcasting of right-truncated epidemiological time-series using a semi-mechanistic Bayesian model with support for a range of reporting and generative processes. Nowcasting, in this context, is gaining situational awareness using currently available observations and the reporting patterns of historical observations. This can be useful when tracking the spread of infectious disease in real-time: without nowcasting, changes in trends can be obfuscated by partial reporting or their detection may be delayed due to the use of simpler methods like truncation. While the package has been designed with epidemiological applications in mind, it could be applied to any set of right-truncated time-series count data.
Maintained by Sam Abbott. Last updated 12 months ago.
cmdstanreffective-reproduction-number-estimationepidemiologyinfectious-disease-surveillancenowcastingoutbreak-analysispandemic-preparednessreal-time-infectious-disease-modellingstan
61 stars 7.79 score 71 scripts
epiforecasts
epinowcast:Flexible Hierarchical Nowcasting
Tools to enable flexible and efficient hierarchical nowcasting of right-truncated epidemiological time-series using a semi-mechanistic Bayesian model with support for a range of reporting and generative processes. Nowcasting, in this context, is gaining situational awareness using currently available observations and the reporting patterns of historical observations. This can be useful when tracking the spread of infectious disease in real-time: without nowcasting, changes in trends can be obfuscated by partial reporting or their detection may be delayed due to the use of simpler methods like truncation. While the package has been designed with epidemiological applications in mind, it could be applied to any set of right-truncated time-series count data.
Maintained by Sam Abbott. Last updated 12 months ago.
cmdstanreffective-reproduction-number-estimationepidemiologyinfectious-disease-surveillancenowcastingoutbreak-analysispandemic-preparednessreal-time-infectious-disease-modellingstan
61 stars 7.58 score 65 scripts
wjakethompson
measr:Bayesian Psychometric Measurement Using 'Stan'
Estimate diagnostic classification models (also called cognitive diagnostic models) with 'Stan'. Diagnostic classification models are confirmatory latent class models, as described by Rupp et al. (2010, ISBN: 978-1-60623-527-0). Automatically generate 'Stan' code for the general loglinear cognitive diagnostic diagnostic model proposed by Henson et al. (2009) <doi:10.1007/s11336-008-9089-5> and other subtypes that introduce additional model constraints. Using the generated 'Stan' code, estimate the model evaluate the model's performance using model fit indices, information criteria, and reliability metrics.
Maintained by W. Jake Thompson. Last updated 3 days ago.
bayesiancdmcmdstanrcognitive-diagnosiscognitive-diagnostic-modelsdcmdiagnostic-classification-modelspsychometricsrstanstancpp
10 stars 6.81 score 31 scripts
fweber144
shinybrms:Graphical User Interface ('shiny' App) for 'brms'
A graphical user interface (GUI) for fitting Bayesian regression models using the package 'brms' which in turn relies on 'Stan' (<https://mc-stan.org/>). The 'shinybrms' GUI is a 'shiny' app.
Maintained by Frank Weber. Last updated 12 months ago.
bayesbayesianbayesian-data-analysisbayesian-inferencebayesian-statisticsbrmscmdstanrguimcmcrstanshinyshiny-appstanstatistical-analysisstatistical-inferencestatistical-modelsstatistics
10 stars 3.70 score 3 scripts