QuasipoissonTrainPredictData: Quasipoisson Core Algorithm

Description Usage Arguments Details

View source: R/QuasipoissonTestPredictData.r

Description

This is the core algorithm of sykdomspulsen.

Usage

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QuasipoissonTrainPredictData(datasetTrain, datasetPredict, reweights = 1,
  remove.pandemic.year = F, remove.highcounts = 0, sign.level = 0.05,
  isDaily = TRUE, v = 1)

Arguments

datasetTrain

Training data.table

datasetPredict

Prediction data.table

reweights

Number (greater or equal to 0) of residual reweights adjusting for previous outbreaks (default: 1; 1 reweight)

remove.pandemic.year

true/false (default: false; keep 2009 data)

remove.highcounts

Number between 0 and 1 of fraction of high counts to be removed from prediction, to remove impact of earlier outbreaks (default: 0)

sign.level

Significance level for the prediction intervals (default: 0.05)

isDaily

Is it daily data or weekly data?

v

Version (Not in use)

Details

Description: Applys a surveillance algorithm based on a quasi-poisson regression model to the selected data. The difference from the Farrington algorithm is in how seasonality is accounted for (here it is adjusted for, in Farrington it is removed by design.


raubreywhite/dashboards_sykdomspuls documentation built on Nov. 17, 2018, 3:16 p.m.