pd_mdsmat: Matrices of weights and distances.
In nenaoana/MDScosa: Multidimensional Scaling (MDS) for COSA data

Description Usage Arguments Author(s)

View source: R/pd_mdsmat.R

Creates matrices of weights and distances, and sets minimum number of observations for parties and issues.

pd_mdsmat <- (
    data,
    party_var,
    issue_var,
    proximity_var,
    year_var,
    years=NULL,
    noweight = FALSE,
    row = FALSE,
    cell = FALSE,
    min = 1,
    imin = NULL
  )

`data`	A dataset containing COSA election campaign data.
`party_var`	Name of the party variable.
`issue_var`	Name of the issue variable.
`proximity_var`	Name of the proximity variable (i.e. direction).
`years`	Years to be included as a vector of characters.
`noweight`	If noweight is TRUE, the matrix of weights is not computed.
`row`	If TRUE, specifies that weights are computed separately for each party (and within each year if the option year is specified).
`cell`	If TRUE, weights are computed separately for each election.
`min`	Minimum number of observations for a party in an election.
`imin`	Minimum percentage of observations for an issue to be included.