Composite 'Indicator' Construction and Imputation Data
Function to get the names of the columns with NAN values
Calculation of Condition Indices
Geometric Aggregation
Function to evaluate different nan imputation methods with bootstrap
Function to evaluate different nan imputation methods
Indicator: A package for constructing composite indicators, imputing a...
Jevons static aggregation
Adjusted Mazziotta-Pareto index
Mazziotta-Pareto index
Linear Aggregation
Function to apply nan inputation with linear regression
Mean absolute difference of rank
Normalization for the Geometric Mean
Min-max normalization
Normalization above or below the mean
Function that weight the quantitative variable by PCA method
Function to evaluate nan imputation method's performance
Ranking Aggregation
Rank normalization
Standardization of data with Adjusted Maziotta-Pareto index
Standardization of data with Maziotta-Pareto index
Standardization
Different functions includes constructing composite indicators, imputing missing data, and evaluating imputation techniques. Additionally, different tools for data normalization. Detailed methodologies of 'Indicator' package are: OECD/European Union/EC-JRC (2008), "Handbook on Constructing Composite Indicators: Methodology and User Guide", OECD Publishing, Paris, <DOI:10.1787/533411815016>, Matteo Mazziotta & Adriano Pareto, (2018) "Measuring Well-Being Over Time: The Adjusted Mazziotta–Pareto Index Versus Other Non-compensatory Indices" <DOI:10.1007/s11205-017-1577-5> and De Muro P., Mazziotta M., Pareto A. (2011), "Composite Indices of Development and Poverty: An Application to MDGs" <DOI:10.1007/s11205-010-9727-z>.
Useful links