rankScatterPlot: Rank Scatter Plot

Description

Generate rank scatter plots for ranking comparison.

Usage

rankScatterPlot(object, p.col = "black", p.size = 1.5, p.shape = 19,
                lab = TRUE, lab.col = "red", lab.size = 3.88,
                ref.line = TRUE, max.overlaps = 10, max.tick = 50,
                ref.lab = "Reference ranking", alt.lab = "Alternative ranking",
                combine = FALSE, nr = NULL, nc = NULL)

Value

A scatter plot displaying unit rankings for two indices. In case object$time

is not NULL, a list of plots for different time factors and the combined grid (if combine = TRUE) will be returned. The function does not print the return if it is assigned to an object. Use print with the storing object to generate the plot.

Arguments

object: an object of class "rankComp", usually, an output of a call to rankComp.
p.col: point color code. See ‘Color Specification’ in par.
p.size: point size value.
p.shape: point shape value. See ‘pch values’ in points.
lab: a logical value indicating whether identifier labels should be assigned to scatter points. If object$id is NULL, the points will be labeled by the row index.
lab.col: color code for labels. See ‘Color Specification’ in par.
lab.size: label size value.
ref.line: a logical value indicating whether a 45-degree reference line should be added to the plot.
max.overlaps: a value to exclude the label if it has too many overlaps. The default value is 10. Set max.overlaps = Inf to always show all labels.
max.tick: a positive integer to control the maximum number of axis ticks. The default value is 50. Set max.tick equal to or greater than the number of rankings to display all rankings on the axis.
ref.lab: name of the reference index.
alt.lab: name of the alternative index.
combine: a logical value indicating whether to generate a grid that combines plots from different time factors (If object$time is not NULL).
nr: (optional) number of rows in the plot grid.
nc: (optional) number of columns in the plot grid.

Author

Viet Duong Nguyen, Chiara Gigliarano, Mariateresa Ciommi

Examples

Run this code

data(bli)

# Goalpost normalization
bli.pol = c("neg", "pos", "pos", "pos", "pos", "neg",
            "pos", "pos", "pos", "neg", "pos")
bli.norm.2014 <- normalize(inds = bli[, 3:13], method = "goalpost",
                           ind.pol = bli.pol, time = bli$YEAR,
                           ref.time = 2014)

# Composite indices
ci.gini <- giniCI(bli.norm.2014, method = "gini",
                  ci.pol = "pos", time = bli$YEAR, ref.time = 2014,
                  only.ci = TRUE)
ci.reci <- giniCI(bli.norm.2014, method = "reci", agg = "geo",
                  ci.pol = "pos", time = bli$YEAR, ref.time = 2014,
                  only.ci = TRUE)

# Ranking comparison plots
ci.comp <- rankComp(ci.gini, ci.reci, id = bli$COUNTRY, time = bli$YEAR)
rankScatterPlot(ci.comp)$'2014'
rankShiftPlot(ci.comp)$'2015'
rankRankPlot(ci.comp)$'2016'

# Storing and printing
p.scatter <- rankScatterPlot(ci.comp, combine = TRUE, max.overlaps = 20)
print(p.scatter$'2017') # or: print(p.scatter[[4]])
print(p.scatter$'comb') # or: print(p.scatter[[5]])

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