parsec-package: PARtial orders in Socio-EConomics
In parsec: PARtial orders in Socio-EConomics
Description
Details
Author(s)
Examples
Description
The package implements basic partial order tools for multidimensional
poverty evaluation with ordinal variables.
Its main goal is to provide socio-economic scholars with an integrated
set of elementary functions for multidimensional poverty evaluation,
based on ordinal information. The package is organized in four main parts.
The first two comprise functions for data management and basic partial order analysis;
the third and the fourth are devoted to evaluation and implement both
the poset-based approach and a more classical counting procedure.
Details
Package: parsec
Type: Package
Version: 1.0
Date: 2013-11-14
License: GPL (>= 2)
Author(s)
A, Arcagni
M, Fattore
Maintainer: A, Arcagni <alberto.arcagni@unimib.it>
Examples
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# a simple example of package application to obtain first poset-based results
# definition of the variables by their number of modalities
variables <- c(2, 2, 2)
# definition of the threshold
threshold <- c("112", "211")
# extraction of all the possible profiles by the variables definition, the
# function returns an object of class "wprof", weighted profiles, by default,
# the wheigths/frequencies are set equal to 1
profiles <- var2prof(varlen = variables)
# the following function creates the matrices that describe the poset, and
# provide all the results related to it
eval <- evaluation(profiles, threshold, nit = 10^5, maxint = 10^3)
# the results can be summarized, the method returns a data.frame object that
# describes the profiles and you can also summarize
summary(summary(eval))
# a method of the plot function returns the Hasse diagram, a frequency
# distribution of the threshold, the identification function, the rank
# distribution of each profile through a barplot, and the relative gap.
plot(eval)
Example output
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Var1 Var2 Var3 weights threshold id. function average rank abs. severity
111 1 1 1 1 FALSE 1.00000 1.00000 3.84535
211 2 1 1 1 TRUE 1.00000 3.33104 1.75243
112 1 1 2 1 TRUE 1.00000 5.09839 1.75548
121 1 2 1 1 FALSE 0.67037 3.33748 1.85316
122 1 2 2 1 FALSE 0.08786 5.66347 0.17572
221 2 2 1 1 FALSE 0.08712 3.91889 0.17424
212 2 1 2 1 FALSE 0.00000 5.65073 0.00000
222 2 2 2 1 FALSE 0.00000 8.00000 0.00000
rel. severity abs. wealth gap rel. wealth gap
111 1.0000000 0.00000 0.0000000
211 0.4595035 0.00000 0.0000000
112 0.4605070 0.00000 0.0000000
121 0.4326725 0.40804 0.0816080
122 0.0351440 2.14702 0.4965733
221 0.0348480 2.16200 0.5001892
212 0.0000000 2.07652 0.4989545
222 0.0000000 4.15465 1.0000000
poverty gap = 0.4037792
wealth gap = 0.515465
inequality has not been evaluated
this function returns a data.frame that summarize each profile
you can also summarize
Var1 Var2 Var3 weights threshold
Min. :1.0 Min. :1.0 Min. :1.0 Min. :1 Mode :logical
1st Qu.:1.0 1st Qu.:1.0 1st Qu.:1.0 1st Qu.:1 FALSE:6
Median :1.5 Median :1.5 Median :1.5 Median :1 TRUE :2
Mean :1.5 Mean :1.5 Mean :1.5 Mean :1
3rd Qu.:2.0 3rd Qu.:2.0 3rd Qu.:2.0 3rd Qu.:1
Max. :2.0 Max. :2.0 Max. :2.0 Max. :1
id. function average rank abs. severity rel. severity
Min. :0.00000 Min. :1.000 Min. :0.0000 Min. :0.00000
1st Qu.:0.06534 1st Qu.:3.336 1st Qu.:0.1307 1st Qu.:0.02614
Median :0.37911 Median :4.509 Median :0.9641 Median :0.23391
Mean :0.48067 Mean :4.500 Mean :1.1945 Mean :0.30283
3rd Qu.:1.00000 3rd Qu.:5.654 3rd Qu.:1.7799 3rd Qu.:0.45975
Max. :1.00000 Max. :8.000 Max. :3.8453 Max. :1.00000
abs. wealth gap rel. wealth gap
Min. :0.000 Min. :0.0000
1st Qu.:0.000 1st Qu.:0.0000
Median :1.242 Median :0.2891
Mean :1.369 Mean :0.3222
3rd Qu.:2.151 3rd Qu.:0.4993
Max. :4.155 Max. :1.0000
parsec documentation built on May 2, 2019, 6:08 p.m.
R Package Documentation
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We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
Description Details Author(s) Examples
Description
The package implements basic partial order tools for multidimensional poverty evaluation with ordinal variables. Its main goal is to provide socio-economic scholars with an integrated set of elementary functions for multidimensional poverty evaluation, based on ordinal information. The package is organized in four main parts. The first two comprise functions for data management and basic partial order analysis; the third and the fourth are devoted to evaluation and implement both the poset-based approach and a more classical counting procedure.
Details
| Package: | parsec |
| Type: | Package |
| Version: | 1.0 |
| Date: | 2013-11-14 |
| License: | GPL (>= 2) |
Author(s)
A, Arcagni M, Fattore
Maintainer: A, Arcagni <alberto.arcagni@unimib.it>
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 | # a simple example of package application to obtain first poset-based results
# definition of the variables by their number of modalities
variables <- c(2, 2, 2)
# definition of the threshold
threshold <- c("112", "211")
# extraction of all the possible profiles by the variables definition, the
# function returns an object of class "wprof", weighted profiles, by default,
# the wheigths/frequencies are set equal to 1
profiles <- var2prof(varlen = variables)
# the following function creates the matrices that describe the poset, and
# provide all the results related to it
eval <- evaluation(profiles, threshold, nit = 10^5, maxint = 10^3)
# the results can be summarized, the method returns a data.frame object that
# describes the profiles and you can also summarize
summary(summary(eval))
# a method of the plot function returns the Hasse diagram, a frequency
# distribution of the threshold, the identification function, the rank
# distribution of each profile through a barplot, and the relative gap.
plot(eval)
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Example output
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Var1 Var2 Var3 weights threshold id. function average rank abs. severity
111 1 1 1 1 FALSE 1.00000 1.00000 3.84535
211 2 1 1 1 TRUE 1.00000 3.33104 1.75243
112 1 1 2 1 TRUE 1.00000 5.09839 1.75548
121 1 2 1 1 FALSE 0.67037 3.33748 1.85316
122 1 2 2 1 FALSE 0.08786 5.66347 0.17572
221 2 2 1 1 FALSE 0.08712 3.91889 0.17424
212 2 1 2 1 FALSE 0.00000 5.65073 0.00000
222 2 2 2 1 FALSE 0.00000 8.00000 0.00000
rel. severity abs. wealth gap rel. wealth gap
111 1.0000000 0.00000 0.0000000
211 0.4595035 0.00000 0.0000000
112 0.4605070 0.00000 0.0000000
121 0.4326725 0.40804 0.0816080
122 0.0351440 2.14702 0.4965733
221 0.0348480 2.16200 0.5001892
212 0.0000000 2.07652 0.4989545
222 0.0000000 4.15465 1.0000000
poverty gap = 0.4037792
wealth gap = 0.515465
inequality has not been evaluated
this function returns a data.frame that summarize each profile
you can also summarize
Var1 Var2 Var3 weights threshold
Min. :1.0 Min. :1.0 Min. :1.0 Min. :1 Mode :logical
1st Qu.:1.0 1st Qu.:1.0 1st Qu.:1.0 1st Qu.:1 FALSE:6
Median :1.5 Median :1.5 Median :1.5 Median :1 TRUE :2
Mean :1.5 Mean :1.5 Mean :1.5 Mean :1
3rd Qu.:2.0 3rd Qu.:2.0 3rd Qu.:2.0 3rd Qu.:1
Max. :2.0 Max. :2.0 Max. :2.0 Max. :1
id. function average rank abs. severity rel. severity
Min. :0.00000 Min. :1.000 Min. :0.0000 Min. :0.00000
1st Qu.:0.06534 1st Qu.:3.336 1st Qu.:0.1307 1st Qu.:0.02614
Median :0.37911 Median :4.509 Median :0.9641 Median :0.23391
Mean :0.48067 Mean :4.500 Mean :1.1945 Mean :0.30283
3rd Qu.:1.00000 3rd Qu.:5.654 3rd Qu.:1.7799 3rd Qu.:0.45975
Max. :1.00000 Max. :8.000 Max. :3.8453 Max. :1.00000
abs. wealth gap rel. wealth gap
Min. :0.000 Min. :0.0000
1st Qu.:0.000 1st Qu.:0.0000
Median :1.242 Median :0.2891
Mean :1.369 Mean :0.3222
3rd Qu.:2.151 3rd Qu.:0.4993
Max. :4.155 Max. :1.0000
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