add.kp.Rd
take a known population vector (see df.to.kpvec
) and
associate it with a survey dataframe. this makes it more convenient
to use some of the networksampling
package's functions
add.kp(survey.data, kp.vec, total.popn.size = NULL)
survey.data | the survey dataframe |
---|---|
kp.vec | the known population vector |
total.popn.size | (optional) the total population size to use (see below) |
the survey dataframe with the known population vector attached as an attribute
The total.popn.size
parameter is interpreted as follows:
NA if total.popn.size is NA then work with proportions
NULL if total.popn.size is NULL (nothing passed in), then assume that there's a total.popn.size attribute associated with the dataset we're using
numerical value if an actual total.popn.size was passed in, use that value
if (FALSE) { # if kp.dat is a dataframe with columns 'kp' with known popn names # and 'total.size' with the total size, # and my.survey is the dataframe with survey responses my.kp.vec <- df.to.kpvec(kp.data, kp.var='kp', kp.value='total.size') my.survey <- add.kp(my.survey, my.kp.vec) # now we can call estimator functions like # kp.degree.estimator without having to specify known # populations each time }