Composite Indicator Construction and Analysis

Documentation for package ‘COINr’ version 1.1.7

Help Pages

-- A --

Aggregate	Aggregate data
Aggregate.coin	Aggregate indicators
Aggregate.data.frame	Aggregate data frame
Aggregate.purse	Aggregate indicators
approx_df	Interpolate time-indexed data frame
ASEM_COIN	ASEM COIN (COINr < v1.0)
ASEM_iData	ASEM raw indicator data
ASEM_iData_p	ASEM raw panel data
ASEM_iMeta	ASEM indicator metadata
a_amean	Weighted arithmetic mean
a_copeland	Copeland scores
a_gmean	Weighted geometric mean
a_hmean	Weighted harmonic mean

-- B --

-- C --

CAGR	Compound annual growth rate
change_ind	Add and remove indicators
check_iData	Check iData
check_iMeta	Check iMeta
check_SkewKurt	Check skew and kurtosis of a vector
COIN_to_coin	Convert a COIN to a coin
compare_coins	Compare two coins
compare_coins_multi	Compare multiple coins
compare_df	Compare two data frames

-- D --

Denominate	Denominate data
Denominate.coin	Denominate data set in a coin
Denominate.data.frame	Denominate data sets by other variables
Denominate.purse	Denominate a data set within a purse.

-- E --

export_to_excel	Export a coin or purse to Excel
export_to_excel.coin	Export a coin to Excel
export_to_excel.purse	Export a purse to Excel

-- G --

get_corr	Get correlations
get_corr_flags	Find highly-correlated indicators within groups
get_cronbach	Cronbach's alpha
get_data	Get subsets of indicator data
get_data.coin	Get subsets of indicator data
get_data.purse	Get subsets of indicator data
get_data_avail	Get data availability of units
get_data_avail.coin	Get data availability of units
get_data_avail.data.frame	Get data availability of units
get_denom_corr	Correlations between indicators and denominators
get_dset	Gets a named data set and performs checks
get_dset.coin	Gets a named data set and performs checks
get_dset.purse	Gets a named data set and performs checks
get_eff_weights	Get effective weights
get_noisy_weights	Noisy replications of weights
get_opt_weights	Weight optimisation
get_PCA	Perform PCA on a coin
get_pvals	P-values for correlations in a data frame or matrix
get_results	Results summary tables
get_sensitivity	Sensitivity and uncertainty analysis of a coin
get_stats	Statistics of columns/indicators
get_stats.coin	Statistics of indicators
get_stats.data.frame	Statistics of columns
get_str_weak	Generate strengths and weaknesses for a specified unit
get_trends	Get time trends
get_unit_summary	Generate unit summary table

-- I --

icodes_to_inames	Convert iCodes to iNames
import_coin_tool	Import data directly from COIN Tool
Impute	Imputation of missing data
Impute.coin	Impute a data set in a coin
Impute.data.frame	Impute a data frame
Impute.numeric	Impute a numeric vector
Impute.purse	Impute data sets in a purse
impute_panel	Impute panel data
is.coin	Check if object is coin class
is.purse	Check if object is purse class
i_mean	Impute by mean
i_mean_grp	Impute by group mean
i_median	Impute by median
i_median_grp	Impute by group median

-- K --

kurt	Calculate kurtosis

-- L --

log_CT	Log-transform a vector
log_CT_orig	Log-transform a vector
log_CT_plus	Log transform a vector (skew corrected)
log_GII	Log-transform a vector

-- N --

names_to_codes	Generate short codes from long names
new_coin	Create a new coin
Normalise	Normalise data
Normalise.coin	Create a normalised data set
Normalise.data.frame	Normalise a data frame
Normalise.numeric	Normalise a numeric vector
Normalise.purse	Create normalised data sets in a purse of coins
n_borda	Normalise using Borda scores
n_dist2max	Normalise as distance to maximum value
n_dist2ref	Normalise as distance to reference value
n_dist2targ	Normalise as distance to target
n_fracmax	Normalise as fraction of max value
n_goalposts	Normalise using goalpost method
n_minmax	Minmax a vector
n_prank	Normalise using percentile ranks
n_rank	Normalise using ranks
n_scaled	Scale a vector
n_zscore	Z-score a vector

-- O --

Outranking matrix

-- P --

plot_bar	Bar chart
plot_corr	Static heatmaps of correlation matrices
plot_dist	Static indicator distribution plots
plot_dot	Dot plots of single indicator with highlighting
plot_framework	Framework plots
plot_scatter	Scatter plot of two variables
plot_sensitivity	Plot sensitivity indices
plot_uncertainty	Plot ranks from an uncertainty/sensitivity analysis
prc_change	Percentage change of time series
print.coin	Print coin
print.purse	Print purse

-- Q --

qNormalise	Quick normalisation
qNormalise.coin	Quick normalisation of a coin
qNormalise.data.frame	Quick normalisation of a data frame
qNormalise.purse	Quick normalisation of a purse
qTreat	Quick outlier treatment
qTreat.coin	Quick outlier treatment of a coin
qTreat.data.frame	Quick outlier treatment of a data frame
qTreat.purse	Quick outlier treatment of a purse

-- R --

rank_df	Convert a data frame to ranks
Regen	Regenerate a coin or purse
Regen.coin	Regenerate a coin
Regen.purse	Regenerate a purse
remove_elements	Check the effect of removing indicators or aggregates
replace_df	Replace multiple values in a data frame
round_df	Round down a data frame

-- S --

SA_estimate	Estimate sensitivity indices
SA_sample	Generate sample for sensitivity analysis
Screen	Screen units based on data availability
Screen.coin	Screen units based on data availability
Screen.data.frame	Screen units based on data availability
Screen.purse	Screen units based on data availability
signif_df	Round a data frame to specified significant figures
skew	Calculate skewness

-- T --

Treat	Treat outliers
Treat.coin	Treat a data set in a coin for outliers
Treat.data.frame	Treat a data frame for outliers
Treat.numeric	Treat a numeric vector for outliers
Treat.purse	Treat a purse of coins for outliers

-- U --

Convert uCodes to uNames

-- W --

winsorise	Winsorise a vector
WorldDenoms	World denomination data