expected_aid_ROI: Expected Value Aid
In itpir/geoSIMEX: geoSIMEX
Description
Usage
Arguments
Details
Note
Author(s)
Examples
Description
expected_aid_ROI Calculates expected value of aid.
Usage
1
expected_aid_ROI(aidData, roiData, probAidAssume, aid.project.amount, aid.precision.code="precision.code", roi.pc1.name="pc1.id", roi.pc2.name="pc2.id", roi.pc3.name="pc3.id", roi.pc4.name="pc4.id", roi.pc5.name="pc5.id", roi.pc6.name="pc6.id", aid.pc1.centroid.name="centroid.pc1.id")
Arguments
aidData
name of dataframe of aid project data
roiData
name of dataframe of ROI data
roi.prob.aid
character containing the name of the variable in the ROI dataset which contains areas of ROIs. "area" is the default name in datasets produced by AidData's data extraction tool
aid.project.amount
character containing the name of the variable in the aidData dataset which contains aid amounts (e.g., commitment, disbursement). Set value to 1 if interested in number of aid projects rather than dollars.
aid.precision.code
character containing the name of the variable in the aidData dataset which contains precision codes for each project. "pc1.id" is the default name in datasets produced by AidData's data extraction tool
roi.pc1.name
character containing the name of the variable in the ROI dataset which contains names or IDs of the precision code 1 spatial area that each ROI falls within. "pc1.id" is the default name in datasets produced by AidData's data extraction tool
roi.pc2.name
character containing the name of the variable in the ROI dataset which contains names or IDs of the precision code 1 spatial area that each ROI falls within. "pc2.id" is the default name in datasets produced by AidData's data extraction tool
roi.pc3.name
character containing the name of the variable in the ROI dataset which contains names or IDs of the precision code 1 spatial area that each ROI falls within. "pc3.id" is the default name in datasets produced by AidData's data extraction tool
roi.pc4.name
character containing the name of the variable in the ROI dataset which contains names or IDs of the precision code 1 spatial area that each ROI falls within. "pc4.id" is the default name in datasets produced by AidData's data extraction tool
roi.pc6.name
character containing the name of the variable in the ROI dataset which contains names or IDs of the precision code 1 spatial area that each ROI falls within. "pc6.id" is the default name in datasets produced by AidData's data extraction tool
aid.pc1.centroid.name
character containing the name of the variable in the aidData dataset which contains names or IDs of a precision code 1 spatial area that the aid project falls within. "centroid.pc1.id" is the default name in datasets produced by AidData's data extraction tool
Details
Calculates expected value of aid for each ROI
Note
The function is built to work with data from AidData's data extration tool. The extraction tool can be accessed here: [provide website].
Author(s)
AidData
Examples
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library(devtools)
install_github("itpir/geoSIMEX")
set.seed(42)
##### Generating Country-Level Dataset #####
numSubcounties <- 120
numSubcountyInCounty <- 2
numCountyInDistrict <- 3
numDistrictInRegion <- 2
N <- numSubcounties
subcounty <- 1:N
county <- rep(1:(N/numSubcountyInCounty), each=numSubcountyInCounty)
district <- rep(1:(N/(numSubcountyInCounty*numCountyInDistrict)), each=(numSubcountyInCounty*numCountyInDistrict))
region <- rep(1:(N/(numSubcountyInCounty*numCountyInDistrict*numDistrictInRegion)), each=(numSubcountyInCounty*numCountyInDistrict*numDistrictInRegion))
country <- 1
subcountyArea <- runif(N)
probAid_assumed <- runif(N)
subcountyData <- as.data.frame(cbind(subcounty,county,district,region,country,probAid_assumed,subcountyArea))
##### Creating Aid Dataset #####
numberProjects = 50
aidData <- as.data.frame(matrix(NA,nrow=numberProjects,ncol=3))
names(aidData) <- c("aid","trueSubcounty","PC")
aidData$aid <- runif(nrow(aidData)) * 100
probAid_true <- runif(N)
aidData$trueSubcounty <- sample(size=numberProjects,x=c(1:N), prob=probAid_true, replace=TRUE)
aidData$PC <- sample(size=numberProjects, x=c(1,2,3,4,6), prob=runif(5), replace=TRUE)
##### Calculating Expected Aid #####
subcountyData$expectedAid <- expected_aid_ROI(aidData=aidData,
aid.project.amount="aid",
aid.precision.code="PC",
aid.pc1.centroid.name="trueSubcounty",
roiData=subcountyData,
roi.prob.aid="probAid_assumed",
roi.pc1.name="subcounty",
roi.pc2.name="county",
roi.pc3.name="district",
roi.pc4.name="region",
roi.pc5.name="region",
roi.pc6.name="country")
itpir/geoSIMEX documentation built on May 18, 2019, 7:10 a.m.
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Description Usage Arguments Details Note Author(s) Examples
Description
expected_aid_ROI Calculates expected value of aid.
Usage
1 | expected_aid_ROI(aidData, roiData, probAidAssume, aid.project.amount, aid.precision.code="precision.code", roi.pc1.name="pc1.id", roi.pc2.name="pc2.id", roi.pc3.name="pc3.id", roi.pc4.name="pc4.id", roi.pc5.name="pc5.id", roi.pc6.name="pc6.id", aid.pc1.centroid.name="centroid.pc1.id")
|
Arguments
aidData |
name of dataframe of aid project data |
roiData |
name of dataframe of ROI data |
roi.prob.aid |
character containing the name of the variable in the ROI dataset which contains areas of ROIs. "area" is the default name in datasets produced by AidData's data extraction tool |
aid.project.amount |
character containing the name of the variable in the aidData dataset which contains aid amounts (e.g., commitment, disbursement). Set value to 1 if interested in number of aid projects rather than dollars. |
aid.precision.code |
character containing the name of the variable in the aidData dataset which contains precision codes for each project. "pc1.id" is the default name in datasets produced by AidData's data extraction tool |
roi.pc1.name |
character containing the name of the variable in the ROI dataset which contains names or IDs of the precision code 1 spatial area that each ROI falls within. "pc1.id" is the default name in datasets produced by AidData's data extraction tool |
roi.pc2.name |
character containing the name of the variable in the ROI dataset which contains names or IDs of the precision code 1 spatial area that each ROI falls within. "pc2.id" is the default name in datasets produced by AidData's data extraction tool |
roi.pc3.name |
character containing the name of the variable in the ROI dataset which contains names or IDs of the precision code 1 spatial area that each ROI falls within. "pc3.id" is the default name in datasets produced by AidData's data extraction tool |
roi.pc4.name |
character containing the name of the variable in the ROI dataset which contains names or IDs of the precision code 1 spatial area that each ROI falls within. "pc4.id" is the default name in datasets produced by AidData's data extraction tool |
roi.pc6.name |
character containing the name of the variable in the ROI dataset which contains names or IDs of the precision code 1 spatial area that each ROI falls within. "pc6.id" is the default name in datasets produced by AidData's data extraction tool |
aid.pc1.centroid.name |
character containing the name of the variable in the aidData dataset which contains names or IDs of a precision code 1 spatial area that the aid project falls within. "centroid.pc1.id" is the default name in datasets produced by AidData's data extraction tool |
Details
Calculates expected value of aid for each ROI
Note
The function is built to work with data from AidData's data extration tool. The extraction tool can be accessed here: [provide website].
Author(s)
AidData
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 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 | library(devtools)
install_github("itpir/geoSIMEX")
set.seed(42)
##### Generating Country-Level Dataset #####
numSubcounties <- 120
numSubcountyInCounty <- 2
numCountyInDistrict <- 3
numDistrictInRegion <- 2
N <- numSubcounties
subcounty <- 1:N
county <- rep(1:(N/numSubcountyInCounty), each=numSubcountyInCounty)
district <- rep(1:(N/(numSubcountyInCounty*numCountyInDistrict)), each=(numSubcountyInCounty*numCountyInDistrict))
region <- rep(1:(N/(numSubcountyInCounty*numCountyInDistrict*numDistrictInRegion)), each=(numSubcountyInCounty*numCountyInDistrict*numDistrictInRegion))
country <- 1
subcountyArea <- runif(N)
probAid_assumed <- runif(N)
subcountyData <- as.data.frame(cbind(subcounty,county,district,region,country,probAid_assumed,subcountyArea))
##### Creating Aid Dataset #####
numberProjects = 50
aidData <- as.data.frame(matrix(NA,nrow=numberProjects,ncol=3))
names(aidData) <- c("aid","trueSubcounty","PC")
aidData$aid <- runif(nrow(aidData)) * 100
probAid_true <- runif(N)
aidData$trueSubcounty <- sample(size=numberProjects,x=c(1:N), prob=probAid_true, replace=TRUE)
aidData$PC <- sample(size=numberProjects, x=c(1,2,3,4,6), prob=runif(5), replace=TRUE)
##### Calculating Expected Aid #####
subcountyData$expectedAid <- expected_aid_ROI(aidData=aidData,
aid.project.amount="aid",
aid.precision.code="PC",
aid.pc1.centroid.name="trueSubcounty",
roiData=subcountyData,
roi.prob.aid="probAid_assumed",
roi.pc1.name="subcounty",
roi.pc2.name="county",
roi.pc3.name="district",
roi.pc4.name="region",
roi.pc5.name="region",
roi.pc6.name="country")
|
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