Example code/some_graphs.r
In edseab/LeadershipModel: Evolutionary simulation of Leadership Strategies
# devtools::install_github("edseab/LeadershipModel")
library(LeadershipModel)
# Vary returns to leadership
plot(seq(0,1,0.1),modl(seq(0,1,0.1),0,L=2,Lavg=2,E=0,Eavg=0),
type = "l", ylim=c(0.4,2),
ylab="Return ratio relative to average",
xlab="Probability of volunteering",
main=c("Vavg=0% P=Pavg=1 E=Eavg=0"))
text(0.45,1,labels="L = 2",srt=-2)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0,L=3,Lavg=3,E=0,Eavg=0))
text(0.4,1.13,labels="L = 3",srt=10)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0,L=1.2,Lavg=1.2,E=0,Eavg=0))
text(0.42,0.89,labels="L = 1",srt=-17)
# Vary average probability of volunteering
plot(seq(0,1,0.1),modl(seq(0,1,0.1),0.1,L=7,Lavg=7,E=0,Eavg=0),
type = "l", ylim=c(0.4,2),
ylab="Return ratio relative to average",
xlab="Probability of volunteering",
main=c("L=Lavg=7 P=Pavg=1 E=Eavg=0"))
text(0.55,1.27,labels="Vavg = 10%",srt=14)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=7,Lavg=7,E=0,Eavg=0))
text(0.6,1.11,labels="Vavg = 20%",srt=6)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.5,L=7,Lavg=7,E=0,Eavg=0))
text(0.65,1.03,labels="Vavg = 50%",srt=-3)
# Vary average leadership of group
plot(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=7,Lavg=7,E=0,Eavg=0),
type = "l", ylim=c(0.4,2),
ylab="Return ratio relative to average",
xlab="Probability of volunteering",
main=c("L=7 P=Pavg=1 E=Eavg=0 Vavg=0.2"))
text(0.54,1.12,labels="Lavg = 5",srt=6)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=7,Lavg=3,E=0,Eavg=0))
text(0.50,1.33,labels="Lavg = 3",srt=17)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=7,Lavg=15,E=0,Eavg=0))
text(0.50,0.93,labels="Lavg = 15",srt=-3)
# Vary productivity
plot(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,E=0,Eavg=0,P=1.4,Pavg=1),
type = "l", ylim=c(0.4,2),
ylab="Return ratio relative to average",
xlab="Probability of volunteering",
main=c("L=5 Pavg=1 E=Eavg=0 Vavg=0.2"))
text(0.55,1.17,labels="P = 1.4",srt=2)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,P=0.8,Pavg=1,E=0,Eavg=0))
text(0.50,1.03,labels="P = 0.8",srt=3)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,P=3,Pavg=1,E=0,Eavg=0))
text(0.50,1.57,labels="P = 3",srt=-4)
# Vary extraction
plot(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,E=0,Eavg=0,P=1,Pavg=1),
type = "l", ylim=c(0.4,2),
ylab="Return ratio relative to average",
xlab="Probability of volunteering",
main=c("L=LAvg=5 P=Pavg=1 Eavg=0 Vavg=0.2"))
text(0.55,1.09,labels="E = 0",srt=2)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,P=1,Pavg=1,E=2,Eavg=0))
text(0.50,1.23,labels="E = 2",srt=9)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,P=1,Pavg=1,E=4,Eavg=0))
text(0.50,1.37,labels="E = 4",srt=14)
# Vary average extraction
plot(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,E=1,Eavg=0,P=3,Pavg=3),
type = "l", ylim=c(0.4,2),
ylab="Return ratio relative to average",
xlab="Probability of volunteering",
main=c("L=Lavg=5 P=Pavg=3 E=1 Vavg=0.2"))
text(0.50,1.06,labels="Eavg = 0",srt=0)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,P=3,Pavg=3,E=1,Eavg=6))
text(0.50,0.97,labels="Eavg = 6",srt=1)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,P=3,Pavg=3,E=1,Eavg=12))
text(0.50,0.88,labels="Eavg = 12",srt=4)
## Now benefits to extraction after being elected ##
# No extraction
plot(seq(0,1,0.1),abdl(seq(0,1,0.1),L=5,Lavg=5,E=0,Eavg=0, P=1,Pavg=1),
lty=1,
type = "l",ylim=c(-1,3),
ylab = "Benefit if leader stays",
xlab = "Average probability of volunteering",
main = "L=Lavg=5 P=Pavg=1 E=Eavg=0"
)
lines(seq(0,1,0.1),overtl(seq(0,1,0.1),L=5,Lavg=5,E=0,Eavg=0, P=1,Pavg=1),
lty=2)
legend(0.4,2.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# Some extraction
plot(seq(0,1,0.1),abdl(seq(0,1,0.1),L=5,Lavg=5,E=1,Eavg=1, P=1,Pavg=1),
lty=1,
type = "l",ylim=c(-1,3),
ylab = "Benefit if leader stays",
xlab = "Average probability of volunteering (Vavg)",
main = "L=Lavg=5 P=Pavg=1 E=Eavg=1"
)
lines(seq(0,1,0.1),overtl(seq(0,1,0.1),L=5,Lavg=5,E=1,Eavg=1, P=1,Pavg=1),
lty=2)
legend(0.4,2.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# More extraction than average
plot(seq(0,1,0.1),abdl(seq(0,1,0.1),L=5,Lavg=5,E=2,Eavg=1, P=1,Pavg=1),
lty=1,
type = "l",ylim=c(-1,3),
ylab = "Benefit if leader stays",
xlab = "Average probability of volunteering (Vavg)",
main = "L=Lavg=5 P=Pavg=1 E=2,Eavg=1"
)
lines(seq(0,1,0.1),overtl(seq(0,1,0.1),L=5,Lavg=5,E=2,Eavg=1, P=1,Pavg=1),
lty=2)
legend(0.4,2.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# See how much extradction a leader can get away with
plot(seq(0,5,0.4),abdl(0.5,L=5,Lavg=5,E=seq(0,5,0.4),Eavg=1, P=1,Pavg=1),
lty=1,
type = "l",ylim=c(-2,3),
ylab = "Benefit if leader stays",
xlab = "Leader extraction E",
main = "Vavg=0.5 L=Lavg=5 P=Pavg=1 Eavg=1"
)
lines(seq(0,5,0.4),overtl(0.5,L=5,Lavg=5,E=seq(0,5,0.4),Eavg=1, P=1,Pavg=1),
lty=2)
legend(0.4,2.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# Higher production than average
plot(seq(0,5,0.4),abdl(0.5,L=5,Lavg=5,E=seq(0,5,0.4),Eavg=1, P=3,Pavg=1),
lty=1,
type = "l",ylim=c(-2,3),
ylab = "Benefit if leader stays",
xlab = "Leader extraction E",
main = "Vavg=0.5 L=Lavg=5 P=3 Pavg=1 Eavg=1"
)
lines(seq(0,5,0.4),overtl(0.5,L=5,Lavg=5,E=seq(0,5,0.4),Eavg=1, P=3,Pavg=1),
lty=2)
legend(0.4,2.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# Higher Leadership than average
plot(seq(0,10,0.4),abdl(0.5,L=6,Lavg=5,E=seq(0,10,0.4),Eavg=1, P=1,Pavg=1),
lty=1,
type = "l",ylim=c(-2,8),
ylab = "Benefit if leader stays",
xlab = "Leader extraction E",
main = "Vavg=0.5 L=6 Lavg=5 Pavg=1 Eavg=1"
)
lines(seq(0,10,0.4),overtl(0.5,L=6,Lavg=5,E=seq(0,10,0.4),Eavg=1, P=1,Pavg=1),
lty=2)
legend(0.4,4.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# Higher Leadership and production
plot(seq(0,10,0.4),abdl(0.5,L=6,Lavg=5,E=seq(0,10,0.4),Eavg=1, P=3,Pavg=1),
lty=1,
type = "l",ylim=c(-2,8),
ylab = "Benefit if leader stays",
xlab = "Leader extraction",
main = "Vavg=0.5 L=6 Lavg=5 P=3 Pavg=1 Eavg=1"
)
lines(seq(0,10,0.4),overtl(0.5,L=6,Lavg=5,E=seq(0,10,0.4),Eavg=1, P=3,Pavg=1),
lty=2)
legend(0.4,4.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# Higher Leadership and production
plot(seq(0,10,0.4),abdl(0.9,L=6,Lavg=5,E=seq(0,10,0.4),Eavg=1, P=3,Pavg=1),
lty=1,
type = "l",ylim=c(-2,8),
ylab = "Benefit if leader stays",
xlab = "Leader extraction",
main = "Vavg=0.9 L=6 Lavg=5 P=3 Pavg=1 Eavg=1"
)
lines(seq(0,10,0.4),overtl(0.9,L=6,Lavg=5,E=seq(0,10,0.4),Eavg=1, P=3,Pavg=1),
lty=2)
legend(0.4,4.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
edseab/LeadershipModel documentation built on Dec. 20, 2021, 3:20 a.m.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
# devtools::install_github("edseab/LeadershipModel")
library(LeadershipModel)
# Vary returns to leadership
plot(seq(0,1,0.1),modl(seq(0,1,0.1),0,L=2,Lavg=2,E=0,Eavg=0),
type = "l", ylim=c(0.4,2),
ylab="Return ratio relative to average",
xlab="Probability of volunteering",
main=c("Vavg=0% P=Pavg=1 E=Eavg=0"))
text(0.45,1,labels="L = 2",srt=-2)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0,L=3,Lavg=3,E=0,Eavg=0))
text(0.4,1.13,labels="L = 3",srt=10)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0,L=1.2,Lavg=1.2,E=0,Eavg=0))
text(0.42,0.89,labels="L = 1",srt=-17)
# Vary average probability of volunteering
plot(seq(0,1,0.1),modl(seq(0,1,0.1),0.1,L=7,Lavg=7,E=0,Eavg=0),
type = "l", ylim=c(0.4,2),
ylab="Return ratio relative to average",
xlab="Probability of volunteering",
main=c("L=Lavg=7 P=Pavg=1 E=Eavg=0"))
text(0.55,1.27,labels="Vavg = 10%",srt=14)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=7,Lavg=7,E=0,Eavg=0))
text(0.6,1.11,labels="Vavg = 20%",srt=6)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.5,L=7,Lavg=7,E=0,Eavg=0))
text(0.65,1.03,labels="Vavg = 50%",srt=-3)
# Vary average leadership of group
plot(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=7,Lavg=7,E=0,Eavg=0),
type = "l", ylim=c(0.4,2),
ylab="Return ratio relative to average",
xlab="Probability of volunteering",
main=c("L=7 P=Pavg=1 E=Eavg=0 Vavg=0.2"))
text(0.54,1.12,labels="Lavg = 5",srt=6)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=7,Lavg=3,E=0,Eavg=0))
text(0.50,1.33,labels="Lavg = 3",srt=17)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=7,Lavg=15,E=0,Eavg=0))
text(0.50,0.93,labels="Lavg = 15",srt=-3)
# Vary productivity
plot(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,E=0,Eavg=0,P=1.4,Pavg=1),
type = "l", ylim=c(0.4,2),
ylab="Return ratio relative to average",
xlab="Probability of volunteering",
main=c("L=5 Pavg=1 E=Eavg=0 Vavg=0.2"))
text(0.55,1.17,labels="P = 1.4",srt=2)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,P=0.8,Pavg=1,E=0,Eavg=0))
text(0.50,1.03,labels="P = 0.8",srt=3)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,P=3,Pavg=1,E=0,Eavg=0))
text(0.50,1.57,labels="P = 3",srt=-4)
# Vary extraction
plot(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,E=0,Eavg=0,P=1,Pavg=1),
type = "l", ylim=c(0.4,2),
ylab="Return ratio relative to average",
xlab="Probability of volunteering",
main=c("L=LAvg=5 P=Pavg=1 Eavg=0 Vavg=0.2"))
text(0.55,1.09,labels="E = 0",srt=2)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,P=1,Pavg=1,E=2,Eavg=0))
text(0.50,1.23,labels="E = 2",srt=9)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,P=1,Pavg=1,E=4,Eavg=0))
text(0.50,1.37,labels="E = 4",srt=14)
# Vary average extraction
plot(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,E=1,Eavg=0,P=3,Pavg=3),
type = "l", ylim=c(0.4,2),
ylab="Return ratio relative to average",
xlab="Probability of volunteering",
main=c("L=Lavg=5 P=Pavg=3 E=1 Vavg=0.2"))
text(0.50,1.06,labels="Eavg = 0",srt=0)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,P=3,Pavg=3,E=1,Eavg=6))
text(0.50,0.97,labels="Eavg = 6",srt=1)
lines(seq(0,1,0.1),modl(seq(0,1,0.1),0.2,L=5,Lavg=5,P=3,Pavg=3,E=1,Eavg=12))
text(0.50,0.88,labels="Eavg = 12",srt=4)
## Now benefits to extraction after being elected ##
# No extraction
plot(seq(0,1,0.1),abdl(seq(0,1,0.1),L=5,Lavg=5,E=0,Eavg=0, P=1,Pavg=1),
lty=1,
type = "l",ylim=c(-1,3),
ylab = "Benefit if leader stays",
xlab = "Average probability of volunteering",
main = "L=Lavg=5 P=Pavg=1 E=Eavg=0"
)
lines(seq(0,1,0.1),overtl(seq(0,1,0.1),L=5,Lavg=5,E=0,Eavg=0, P=1,Pavg=1),
lty=2)
legend(0.4,2.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# Some extraction
plot(seq(0,1,0.1),abdl(seq(0,1,0.1),L=5,Lavg=5,E=1,Eavg=1, P=1,Pavg=1),
lty=1,
type = "l",ylim=c(-1,3),
ylab = "Benefit if leader stays",
xlab = "Average probability of volunteering (Vavg)",
main = "L=Lavg=5 P=Pavg=1 E=Eavg=1"
)
lines(seq(0,1,0.1),overtl(seq(0,1,0.1),L=5,Lavg=5,E=1,Eavg=1, P=1,Pavg=1),
lty=2)
legend(0.4,2.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# More extraction than average
plot(seq(0,1,0.1),abdl(seq(0,1,0.1),L=5,Lavg=5,E=2,Eavg=1, P=1,Pavg=1),
lty=1,
type = "l",ylim=c(-1,3),
ylab = "Benefit if leader stays",
xlab = "Average probability of volunteering (Vavg)",
main = "L=Lavg=5 P=Pavg=1 E=2,Eavg=1"
)
lines(seq(0,1,0.1),overtl(seq(0,1,0.1),L=5,Lavg=5,E=2,Eavg=1, P=1,Pavg=1),
lty=2)
legend(0.4,2.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# See how much extradction a leader can get away with
plot(seq(0,5,0.4),abdl(0.5,L=5,Lavg=5,E=seq(0,5,0.4),Eavg=1, P=1,Pavg=1),
lty=1,
type = "l",ylim=c(-2,3),
ylab = "Benefit if leader stays",
xlab = "Leader extraction E",
main = "Vavg=0.5 L=Lavg=5 P=Pavg=1 Eavg=1"
)
lines(seq(0,5,0.4),overtl(0.5,L=5,Lavg=5,E=seq(0,5,0.4),Eavg=1, P=1,Pavg=1),
lty=2)
legend(0.4,2.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# Higher production than average
plot(seq(0,5,0.4),abdl(0.5,L=5,Lavg=5,E=seq(0,5,0.4),Eavg=1, P=3,Pavg=1),
lty=1,
type = "l",ylim=c(-2,3),
ylab = "Benefit if leader stays",
xlab = "Leader extraction E",
main = "Vavg=0.5 L=Lavg=5 P=3 Pavg=1 Eavg=1"
)
lines(seq(0,5,0.4),overtl(0.5,L=5,Lavg=5,E=seq(0,5,0.4),Eavg=1, P=3,Pavg=1),
lty=2)
legend(0.4,2.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# Higher Leadership than average
plot(seq(0,10,0.4),abdl(0.5,L=6,Lavg=5,E=seq(0,10,0.4),Eavg=1, P=1,Pavg=1),
lty=1,
type = "l",ylim=c(-2,8),
ylab = "Benefit if leader stays",
xlab = "Leader extraction E",
main = "Vavg=0.5 L=6 Lavg=5 Pavg=1 Eavg=1"
)
lines(seq(0,10,0.4),overtl(0.5,L=6,Lavg=5,E=seq(0,10,0.4),Eavg=1, P=1,Pavg=1),
lty=2)
legend(0.4,4.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# Higher Leadership and production
plot(seq(0,10,0.4),abdl(0.5,L=6,Lavg=5,E=seq(0,10,0.4),Eavg=1, P=3,Pavg=1),
lty=1,
type = "l",ylim=c(-2,8),
ylab = "Benefit if leader stays",
xlab = "Leader extraction",
main = "Vavg=0.5 L=6 Lavg=5 P=3 Pavg=1 Eavg=1"
)
lines(seq(0,10,0.4),overtl(0.5,L=6,Lavg=5,E=seq(0,10,0.4),Eavg=1, P=3,Pavg=1),
lty=2)
legend(0.4,4.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
# Higher Leadership and production
plot(seq(0,10,0.4),abdl(0.9,L=6,Lavg=5,E=seq(0,10,0.4),Eavg=1, P=3,Pavg=1),
lty=1,
type = "l",ylim=c(-2,8),
ylab = "Benefit if leader stays",
xlab = "Leader extraction",
main = "Vavg=0.9 L=6 Lavg=5 P=3 Pavg=1 Eavg=1"
)
lines(seq(0,10,0.4),overtl(0.9,L=6,Lavg=5,E=seq(0,10,0.4),Eavg=1, P=3,Pavg=1),
lty=2)
legend(0.4,4.5,lty=1:2,legend=c("Benefit to leader","Benefit to group"))
abline(h=0, col='darkred')
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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