mem (version 2.5)

transformdata: Data transformation

Description

Function transformdata transforms data from year,week,rate to week,rate1,...,rateN suitable to use with mem.

Usage

transformdata(i.data, i.range.x = NA, i.name = "rates",
  i.max.na.per = 100)

Arguments

i.data

Data frame of input data.

i.range.x

First and last surveillance week.

i.name

Name of the column to transform.

i.max.na.per

maximum percentage of na's in a season allowable, otherwise, the season is removed

Value

transformdata returns a data.frame where each column has a different season and rownames are the name of the epidemiological week.

Details

Yet to be written

References

Vega Alonso, Tomas, Jose E Lozano Alonso, Raul Ortiz de Lejarazu, and Marisol Gutierrez Perez. 2004. Modelling Influenza Epidemic: Can We Detect the Beginning and Predict the Intensity and Duration? International Congress Series, Options for the Control of Influenza V. Proceedings of the International Conference on Options for the Control of Influenza V, 1263 (June): 281-83. doi:10.1016/j.ics.2004.02.121. Vega, Tomas, Jose Eugenio Lozano, Tamara Meerhoff, Rene Snacken, Joshua Mott, Raul Ortiz de Lejarazu, and Baltazar Nunes. 2013. Influenza Surveillance in Europe: Establishing Epidemic Thresholds by the Moving Epidemic Method. Influenza and Other Respiratory Viruses 7 (4): 546-58. doi:10.1111/j.1750-2659.2012.00422.x. Vega, Tomas, Jose E. Lozano, Tamara Meerhoff, Rene Snacken, Julien Beaute, Pernille Jorgensen, Raul Ortiz de Lejarazu, et al. 2015. Influenza Surveillance in Europe: Comparing Intensity Levels Calculated Using the Moving Epidemic Method. Influenza and Other Respiratory Viruses 9 (5): 234-46. doi:10.1111/irv.12330.

Examples

# Castilla y Leon Influenza Rates data
data(flucylraw)
# Transform data
newdata<-transformdata(flucylraw, i.range.x=c(40,20))$data
epi<-memmodel(newdata)
print(epi)
summary(epi)
plot(epi)