jackstrap_ks {jackstrap}

Jackstrap KS Method: Tool identifies outliers in Nonparametric Frontier. This function applies the developed technique by Sousa and Stosic (2005) Technical Efficiency of the Brazilian Municipalities: Correcting Nonparametric Frontier Meansurements for Outliers and to use the K-S test with criterion to define outliers.

Description

Jackstrap KS Method: Tool identifies outliers in Nonparametric Frontier. This function applies the developed technique by Sousa and Stosic (2005) Technical Efficiency of the Brazilian Municipalities: Correcting Nonparametric Frontier Meansurements for Outliers and to use the K-S test with criterion to define outliers.

Usage

jackstrap_ks(data, jackstrap_obj, num_cores = 1, perc = 0.9)

Arguments

data

is the dataset with input and output used to measure efficiency; Dataset need to have this form: 1th column: name of DMU (string); 2th column: code of DMU (integer); n columns of output variables; n columns of input variables.

jackstrap_obj

is the object created by the function jackstrap.

num_cores

is the number of cores available to process.

perc

is the percentage of DMU analyzed by K-S test.

Value

Return the jackstrap object increased with informations as follows: "result_kstest_method" is p-values of K-S test obtained by removing sequencially one by one the high leverage DMU; "efficiency_ks_method" is efficiency indicators obtained by K-S test criterion.

Examples

 
 
    #Command measures efficiency with jackstrap method and K-S test criterion
    efficiency_ks <- jackstrap_ks (data=municipalities, jackstrap_obj=efficiency,
                                   num_cores = 4)