isoWeekYear

formatDate

Date object (POSIX) or the year. Can be a vector.

month, <code>NULL</code> if Y is a Date object)

day, <code>NULL</code> if Y is a Date object)

This function extracts the ISO week and ISO year of a <code>Date</code>
  according to the ISO 8601 specification. Note that this function
  does nothing else than format.Date(x, "%G") and format.Date(x, "%V")
  would do on Mac/Unix computers. However, this is not implemented
  on Windows.<p></p><p>  A small internal wrapper for <code>format.Date</code> (called
  <code>formatDate</code>) thus directs all calls having one of these format
  strings to this function, if the <code>sessionInfo()[[1]]$os</code>
  information reveals a Windows system. The function also provides three
  additional <code>strptime</code> formatting strings: "%Q" (the quarter of a
  date as a numeric), "  (day within the quarter). These are, e.g., used by <code>linelist2sts</code>.</p>

chron

A package implementing statistical methods for the modeling and
        change-point detection in time series of counts, proportions and
        categorical data, as well as for the modeling of continuous-time
        epidemic phenomena, e.g. discrete-space setups such as the spatially
        enriched Susceptible-Exposed-Infectious-Recovered (SEIR) models for
        surveillance data, or continuous-space point process data such as the
        occurrence of disease or earthquakes. Main focus is on outbreak
        detection in count data time series originating from public health
        surveillance of infectious diseases, but applications could just as well
        originate from environmetrics, reliability engineering, econometrics or
        social sciences.
        Currently the package contains implementations of typical
        outbreak detection procedures such as Farrington et al (1996),
        Noufaily et al (2012) or the negative binomial LR-CUSUM method
        described in Hoehle and Paul (2008). Furthermore, inference
        methods for the retrospective infectious disease model in Held
        et al (2005), Held et al (2006), Paul et al (2008) and Paul
        and Held (2011) are provided. A novel CUSUM approach combining
        logistic and multinomial logistic modelling is also included.
        Continuous self-exciting spatio-temporal point processes are
        modeled through additive-multiplicative conditional
        intensities as described in H�hle (2009) ("twinSIR", discrete
        space) and Meyer et al (2012) ("twinstim", continuous space).
        The package contains several real-world data sets, the ability
        to simulate outbreak data, visualize the results of the
        monitoring in temporal, spatial or spatio-temporal fashion.
	Note: Using the 'boda' algorithm requires the the INLA
        package, which should be installed automatically through the
        specified Additional_repositories, if uninstalled dependencies
        are also requested. As this might not work under Mac OS X it
        might be necessary to manually install the INLA package as
        specified at http://www.r-inla.org/download.

isoWeekYear: Find ISO week and ISO year of a vector of Date objects on Windows

Description

Usage

Arguments

Value

Details

Examples