GiniWegNeg
Computing the Gini-Based Coefficients for Weighted and Negative Attributes

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GRSVc: Generalized RSV (Raffinetti, Siletti and Vernizzi, 2015)...

GRSVc: Generalized RSV (Raffinetti, Siletti and Vernizzi, 2015)...
In GiniWegNeg: Computing the Gini-Based Coefficients for Weighted and Negative Attributes

Description Usage Arguments Details Value Note Author(s) References See Also Examples

View source: R/GRSVc.R

Description

computes the x-axis and y-axis values of the generalized RSV curve of maximum inequality for negative attributes.

Usage

1
GRSVc(z,w=rep(1,length(z)),plot=FALSE)

Arguments

z

a vector of attributes containing negative elements

w

a vector containing the weights associated with the elements of the attribute vector

plot

logical. If TRUE the generalized RSV curve of maximum inequality is plotted

Details

GRSVc(z,w) provides the points of the generalized RSV curve of maximum inequality.

Value

A list of class GRSVc with the following components:

Generalized RSV (maximum inequality) x-axis points

vector with the x-axis values of the generalized RSV curve of maximum inequality

Generalized RSV (maximum inequality) y-axis points

vector with the y-axis values of the generalized RSV curve of maximum inequality.

Note

If the vector w contains unitary elements, the plot of the generalized RSV curve of maximum inequality is obtained as GRSVc(z,plot=TRUE).

Author(s)

Emanuela Raffinetti, Fabio Aimar

References

E. Raffinetti, E. Siletti, A. Vernizzi (2014), Inequality measures and the issue of negative income. Italian Statistical Society Conference (SIS), Book of Short Papers: "SIS2014. 47th Scientific Meeting of the Italian Statistical Society", CUEC (Cooperativa Universitaria Editrice Cagliaritana), 11-13 June 2014

E. Raffinetti, E. Siletti, A. Vernizzi (2015), On the Gini coefficient normalization when incomes with negative values are considered, Statistical Methods & Applications, 24(3), 507-521

See Also

ineq, IC2

Examples

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# generate the vector of attributes with even negative elements
z<-c(-7,-15,11,-10,2,4,40)
# plot the generalized RSV curve of maximum inequality
GRSVc(z,plot=TRUE) 

# generate the vector of attributes with even negative elements
z<-c(10,-25,-12,3,2,-5,45)
# generate the vector of non-unitary weights
w<-c(1.5,2.2,1.9,3.8,4.7,5,2.3)
# plot the generalized RSV curve of maximum inequality
GRSVc(z,w,plot=TRUE) 

data(BI2012)
# define the vector of non-unitary weights
w<-BI2012$weight 

# select the vector of incomes (e.g., the incomes from transfers YTA)
z<-BI2012$YTA
# plot the generalized RSV curve of maximum inequality
GRSVc(z,w,plot=TRUE) 

# select the vector of incomes (e.g., the incomes from financial capital gain YCF)
z<-BI2012$YCF
# plot the generalized RSV curve of maximum inequality
GRSVc(z,w,plot=TRUE)

Example output

$`Generalized RSV (maximum inequality) x-axis points`
[1] 0.0000000 0.1428571 0.2857143 0.4285714 0.5714286 0.7142857 0.8571429
[8] 1.0000000

$`Generalized RSV (maximum inequality) y-axis points`
[1]  0.000000 -4.571429 -4.571429 -4.571429 -4.571429 -4.571429 -4.571429
[8]  3.571429

$`Generalized RSV (maximum inequality) x-axis points`
[1] 0.00000000 0.07009346 0.17289720 0.26168224 0.43925234 0.65887850 0.89252336
[8] 1.00000000

$`Generalized RSV (maximum inequality) y-axis points`
[1]  0.000000 -4.803738 -4.803738 -4.803738 -4.803738 -4.803738 -4.803738
[8]  1.705607

$`Generalized RSV (maximum inequality) x-axis points`
  [1] 0.000000000 0.002793724 0.009800403 0.012653261 0.016247102 0.017533666
  [7] 0.040996217 0.043388341 0.050347197 0.073820033 0.078678326 0.080427168
 [13] 0.081154780 0.082176523 0.084134136 0.106256646 0.111961335 0.127178981
 [19] 0.129607614 0.131203219 0.138652122 0.147510485 0.149741659 0.153199747
 [25] 0.159073613 0.183109513 0.185721720 0.187714813 0.196980433 0.211448355
 [31] 0.218071945 0.219338454 0.223744752 0.227368418 0.228701774 0.235806154
 [37] 0.237370907 0.240447963 0.243474111 0.247477781 0.249852935 0.255902661
 [43] 0.259575177 0.261253057 0.265895380 0.266720693 0.270309392 0.271289484
 [49] 0.273396732 0.275024219 0.278589264 0.280143219 0.282488034 0.286017084
 [55] 0.286969408 0.295621057 0.303374374 0.305671368 0.311587913 0.316100654
 [61] 0.316100654 0.318329772 0.319200850 0.320487413 0.323697650 0.326336596
 [67] 0.329958205 0.332165725 0.335123998 0.336136485 0.344075947 0.346393509
 [73] 0.348256506 0.351659574 0.353505602 0.359149614 0.364942233 0.366657651
 [79] 0.370253034 0.371816245 0.378410009 0.385897992 0.388570362 0.396310310
 [85] 0.396889829 0.399482495 0.409130691 0.412543014 0.414444063 0.417674869
 [91] 0.421182322 0.423012409 0.426342458 0.432337678 0.448784810 0.455867078
 [97] 0.465190804 0.466604378 0.466604378 0.476536420 0.483224286 0.485210180
[103] 0.485975844 0.490212967 0.493444801 0.496822158 0.499284728 0.500719899
[109] 0.509965980 0.519862026 0.522042807 0.525557459 0.553927154 0.554862509
[115] 0.556076569 0.563872051 0.565610608 0.568039241 0.582204805 0.583508337
[121] 0.603507659 0.607302557 0.609040600 0.610338476 0.614733462 0.634891161
[127] 0.636447173 0.637362473 0.650772658 0.657871381 0.660466618 0.663222291
[133] 0.665093001 0.667994196 0.685583396 0.696343322 0.700978960 0.703960373
[139] 0.703960373 0.716038229 0.716998780 0.724230170 0.728124826 0.729893208
[145] 0.731831794 0.746142882 0.755165279 0.756576282 0.760768153 0.761960615
[151] 0.766072270 0.768489589 0.769765868 0.771253489 0.783015103 0.784527921
[157] 0.787405976 0.789497798 0.795729042 0.798204468 0.800148196 0.801181766
[163] 0.808200272 0.809546998 0.812797858 0.830851908 0.834075515 0.837523834
[169] 0.839772491 0.842578556 0.846267013 0.850413634 0.855391738 0.858111930
[175] 0.861207498 0.869333620 0.877994525 0.897109398 0.913158528 0.916363109
[181] 0.920651139 0.921647685 0.927029962 0.929730614 0.931267599 0.934481950
[187] 0.935897581 0.940582070 0.943219473 0.949608066 0.951285946 0.953675498
[193] 0.955271104 0.956542241 0.967934135 0.970536572 0.979177422 0.981700670
[199] 0.994517966 0.996942998 1.000000000

$`Generalized RSV (maximum inequality) y-axis points`
  [1]    0.0000 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
  [8] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
 [15] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
 [22] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
 [29] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
 [36] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
 [43] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
 [50] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
 [57] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
 [64] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
 [71] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
 [78] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
 [85] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
 [92] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
 [99] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[106] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[113] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[120] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[127] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[134] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[141] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[148] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[155] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[162] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[169] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[176] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[183] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[190] -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105 -133.3105
[197] -133.3105 -133.3105 -133.3105 -133.3105  162.5800

$`Generalized RSV (maximum inequality) x-axis points`
  [1] 0.000000000 0.002793724 0.009800403 0.012653261 0.016247102 0.017533666
  [7] 0.040996217 0.043388341 0.050347197 0.073820033 0.078678326 0.080427168
 [13] 0.081154780 0.082176523 0.084134136 0.106256646 0.111961335 0.127178981
 [19] 0.129607614 0.131203219 0.138652122 0.147510485 0.149741659 0.153199747
 [25] 0.159073613 0.183109513 0.185721720 0.187714813 0.196980433 0.211448355
 [31] 0.218071945 0.219338454 0.223744752 0.227368418 0.228701774 0.235806154
 [37] 0.237370907 0.240447963 0.243474111 0.247477781 0.249852935 0.255902661
 [43] 0.259575177 0.261253057 0.265895380 0.266720693 0.270309392 0.271289484
 [49] 0.273396732 0.275024219 0.278589264 0.280143219 0.282488034 0.286017084
 [55] 0.286969408 0.295621057 0.303374374 0.305671368 0.311587913 0.316100654
 [61] 0.316100654 0.318329772 0.319200850 0.320487413 0.323697650 0.326336596
 [67] 0.329958205 0.332165725 0.335123998 0.336136485 0.344075947 0.346393509
 [73] 0.348256506 0.351659574 0.353505602 0.359149614 0.364942233 0.366657651
 [79] 0.370253034 0.371816245 0.378410009 0.385897992 0.388570362 0.396310310
 [85] 0.396889829 0.399482495 0.409130691 0.412543014 0.414444063 0.417674869
 [91] 0.421182322 0.423012409 0.426342458 0.432337678 0.448784810 0.455867078
 [97] 0.465190804 0.466604378 0.466604378 0.476536420 0.483224286 0.485210180
[103] 0.485975844 0.490212967 0.493444801 0.496822158 0.499284728 0.500719899
[109] 0.509965980 0.519862026 0.522042807 0.525557459 0.553927154 0.554862509
[115] 0.556076569 0.563872051 0.565610608 0.568039241 0.582204805 0.583508337
[121] 0.603507659 0.607302557 0.609040600 0.610338476 0.614733462 0.634891161
[127] 0.636447173 0.637362473 0.650772658 0.657871381 0.660466618 0.663222291
[133] 0.665093001 0.667994196 0.685583396 0.696343322 0.700978960 0.703960373
[139] 0.703960373 0.716038229 0.716998780 0.724230170 0.728124826 0.729893208
[145] 0.731831794 0.746142882 0.755165279 0.756576282 0.760768153 0.761960615
[151] 0.766072270 0.768489589 0.769765868 0.771253489 0.783015103 0.784527921
[157] 0.787405976 0.789497798 0.795729042 0.798204468 0.800148196 0.801181766
[163] 0.808200272 0.809546998 0.812797858 0.830851908 0.834075515 0.837523834
[169] 0.839772491 0.842578556 0.846267013 0.850413634 0.855391738 0.858111930
[175] 0.861207498 0.869333620 0.877994525 0.897109398 0.913158528 0.916363109
[181] 0.920651139 0.921647685 0.927029962 0.929730614 0.931267599 0.934481950
[187] 0.935897581 0.940582070 0.943219473 0.949608066 0.951285946 0.953675498
[193] 0.955271104 0.956542241 0.967934135 0.970536572 0.979177422 0.981700670
[199] 0.994517966 0.996942998 1.000000000

$`Generalized RSV (maximum inequality) y-axis points`
  [1]   0.00000 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
  [8] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
 [15] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
 [22] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
 [29] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
 [36] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
 [43] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
 [50] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
 [57] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
 [64] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
 [71] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
 [78] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
 [85] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
 [92] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
 [99] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[106] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[113] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[120] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[127] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[134] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[141] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[148] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[155] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[162] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[169] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[176] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[183] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[190] -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488 -68.20488
[197] -68.20488 -68.20488 -68.20488 -68.20488 148.31140

GiniWegNeg documentation built on May 2, 2019, 6:10 a.m.

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