surveillance: create.disProg – R documentation

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create.disProg

Creating an object of class disProg

Description

Creates an object of class disProg from a vector with the weeknumber (week) and matrices with the observed number of counts (observed) and the respective state chains (state), where each column represents an individual time series. The matrices neighbourhood and populationFrac provide information about neighbouring units and population proportions.

Usage

create.disProg(week, observed, state, start=c(2001,1), freq=52, 
               neighbourhood=NULL, populationFrac=NULL, epochAsDate=FALSE)

Arguments

`week`	index in the matrix of observations, typically weeks
`observed`	matrix with parallel time series of counts where rows are time points and columns are the individual time series for unit/area i, i=1,…,m
`state`	matrix with corresponding states
`start`	vector of length two denoting the year and the sample number (week, month, etc.) of the first observation
`freq`	sampling frequency per year, i.e. 52 for weekly data, 12 for monthly data, 13 if 52 weeks are aggregated into 4 week blocks.
`neighbourhood`	neighbourhood matrix N of dimension m \times m with elements n_{ij}=1 if units i and j are adjacent and 0 otherwise
`populationFrac`	matrix with corresponding population proportions
`epochAsDate`	interpret the integers in `week` as Dates. Default is `FALSE`

Value

object of class disProg

Author(s)

M. Paul

Examples

# create an univariate disProg object 
# read in salmonella.agona data
salmonella <- read.table(system.file("extdata/salmonella.agona.txt", 
                                     package = "surveillance"), header = TRUE)
# look at data.frame
str(salmonella)

salmonellaDisProg <- create.disProg(week = 1:nrow(salmonella), 
                                    observed = salmonella$observed,
                                    state = salmonella$state,
                                    start = c(1990, 1))

# look at disProg object
salmonellaDisProg

surveillance

Temporal and Spatio-Temporal Modeling and Monitoring of Epidemic Phenomena

v1.19.1

GPL-2

Authors

Michael H<f6>hle [aut, ths] (<https://orcid.org/0000-0002-0423-6702>), Sebastian Meyer [aut, cre] (<https://orcid.org/0000-0002-1791-9449>), Michaela Paul [aut], Leonhard Held [ctb, ths], Howard Burkom [ctb], Thais Correa [ctb], Mathias Hofmann [ctb], Christian Lang [ctb], Juliane Manitz [ctb], Andrea Riebler [ctb], Daniel Saban<e9>s Bov<e9> [ctb], Ma<eb>lle Salmon [ctb], Dirk Schumacher [ctb], Stefan Steiner [ctb], Mikko Virtanen [ctb], Wei Wei [ctb], Valentin Wimmer [ctb], R Core Team [ctb] (A few code segments are modified versions of code from base R)

Initial release

2021-03-30