Plots of prior and posterior distributions for a model
0
$begingroup$
I have an exercise that ask to plot the prior and posterior distribution in the Poisson-Gamma model. I did it (I think it's correct) inspired
in the answer of this question https://stats.stackexchange.com/questions/70661/how-does-the-beta-prior-affect-the-posterior-under-a-binomial-likelihood
Is there anything that can improve the code?
colors = c("red","blue","green","orange","purple")
n = 10
lambda = .2
x = rpois(n,lambda)
grid = seq(0,2,.01)
alpha = c(.5,5,1,2,2)
beta = c(.5,1,3,2,5)
plot(grid,grid,type="n",xlim=c(0,1),ylim=c(0,4),xlab="",ylab="Prior Density",
main="Prior Distributions", las=1)
for(i in 1:length(alpha)){
prior = dgamma(grid,alpha[i],1/beta[i])
lines(grid,prior,col=colors[i],lwd=2)
}
legend("topleft", legend=c("Gamma(0.5,0.5)", "Gamma(5,1)", "Gamma(1,3)", "Gamma(2,2)", "Gamma(2,5)"),
lwd=rep(2,5), col=colors, bty="n", ncol=3)
for(i in 1:length(alpha)){
dev.new()
plot(grid,grid,type="n",xlim=c(0,1),ylim=c(0,10),xlab="",ylab="Density",xaxs="i",yaxs="i",
main="Prior and Posterior Distribution")
alpha.star = alpha[i] + sum(x)
beta.star = beta[i] + n
prior = dgamma(grid,alpha[i],beta[i])
post = dgamma(grid,alpha.star,beta.star)
lines(grid,post,lwd=2)
lines(grid,prior,col=colors[i],lwd=2)
legend("topright",c("Prior","Posterior"),col=c(colors[i],"black"),lwd=2)
}
beginner statistics r
asked 22 mins ago
MichelleMichelle
231112
$endgroup$
add a comment |
0
$begingroup$
I have an exercise that ask to plot the prior and posterior distribution in the Poisson-Gamma model. I did it (I think it's correct) inspired
in the answer of this question https://stats.stackexchange.com/questions/70661/how-does-the-beta-prior-affect-the-posterior-under-a-binomial-likelihood
Is there anything that can improve the code?
colors = c("red","blue","green","orange","purple")
n = 10
lambda = .2
x = rpois(n,lambda)
grid = seq(0,2,.01)
alpha = c(.5,5,1,2,2)
beta = c(.5,1,3,2,5)
plot(grid,grid,type="n",xlim=c(0,1),ylim=c(0,4),xlab="",ylab="Prior Density",
main="Prior Distributions", las=1)
for(i in 1:length(alpha)){
prior = dgamma(grid,alpha[i],1/beta[i])
lines(grid,prior,col=colors[i],lwd=2)
}
legend("topleft", legend=c("Gamma(0.5,0.5)", "Gamma(5,1)", "Gamma(1,3)", "Gamma(2,2)", "Gamma(2,5)"),
lwd=rep(2,5), col=colors, bty="n", ncol=3)
for(i in 1:length(alpha)){
dev.new()
plot(grid,grid,type="n",xlim=c(0,1),ylim=c(0,10),xlab="",ylab="Density",xaxs="i",yaxs="i",
main="Prior and Posterior Distribution")
alpha.star = alpha[i] + sum(x)
beta.star = beta[i] + n
prior = dgamma(grid,alpha[i],beta[i])
post = dgamma(grid,alpha.star,beta.star)
lines(grid,post,lwd=2)
lines(grid,prior,col=colors[i],lwd=2)
legend("topright",c("Prior","Posterior"),col=c(colors[i],"black"),lwd=2)
}
beginner statistics r
asked 22 mins ago
MichelleMichelle
231112
$endgroup$
add a comment |
0
0
0
$begingroup$
I have an exercise that ask to plot the prior and posterior distribution in the Poisson-Gamma model. I did it (I think it's correct) inspired
in the answer of this question https://stats.stackexchange.com/questions/70661/how-does-the-beta-prior-affect-the-posterior-under-a-binomial-likelihood
Is there anything that can improve the code?
colors = c("red","blue","green","orange","purple")
n = 10
lambda = .2
x = rpois(n,lambda)
grid = seq(0,2,.01)
alpha = c(.5,5,1,2,2)
beta = c(.5,1,3,2,5)
plot(grid,grid,type="n",xlim=c(0,1),ylim=c(0,4),xlab="",ylab="Prior Density",
main="Prior Distributions", las=1)
for(i in 1:length(alpha)){
prior = dgamma(grid,alpha[i],1/beta[i])
lines(grid,prior,col=colors[i],lwd=2)
}
legend("topleft", legend=c("Gamma(0.5,0.5)", "Gamma(5,1)", "Gamma(1,3)", "Gamma(2,2)", "Gamma(2,5)"),
lwd=rep(2,5), col=colors, bty="n", ncol=3)
for(i in 1:length(alpha)){
dev.new()
plot(grid,grid,type="n",xlim=c(0,1),ylim=c(0,10),xlab="",ylab="Density",xaxs="i",yaxs="i",
main="Prior and Posterior Distribution")
alpha.star = alpha[i] + sum(x)
beta.star = beta[i] + n
prior = dgamma(grid,alpha[i],beta[i])
post = dgamma(grid,alpha.star,beta.star)
lines(grid,post,lwd=2)
lines(grid,prior,col=colors[i],lwd=2)
legend("topright",c("Prior","Posterior"),col=c(colors[i],"black"),lwd=2)
}
beginner statistics r
asked 22 mins ago
MichelleMichelle
231112
$endgroup$
I have an exercise that ask to plot the prior and posterior distribution in the Poisson-Gamma model. I did it (I think it's correct) inspired
in the answer of this question https://stats.stackexchange.com/questions/70661/how-does-the-beta-prior-affect-the-posterior-under-a-binomial-likelihood
Is there anything that can improve the code?
colors = c("red","blue","green","orange","purple")
n = 10
lambda = .2
x = rpois(n,lambda)
grid = seq(0,2,.01)
alpha = c(.5,5,1,2,2)
beta = c(.5,1,3,2,5)
plot(grid,grid,type="n",xlim=c(0,1),ylim=c(0,4),xlab="",ylab="Prior Density",
main="Prior Distributions", las=1)
for(i in 1:length(alpha)){
prior = dgamma(grid,alpha[i],1/beta[i])
lines(grid,prior,col=colors[i],lwd=2)
}
legend("topleft", legend=c("Gamma(0.5,0.5)", "Gamma(5,1)", "Gamma(1,3)", "Gamma(2,2)", "Gamma(2,5)"),
lwd=rep(2,5), col=colors, bty="n", ncol=3)
for(i in 1:length(alpha)){
dev.new()
plot(grid,grid,type="n",xlim=c(0,1),ylim=c(0,10),xlab="",ylab="Density",xaxs="i",yaxs="i",
main="Prior and Posterior Distribution")
alpha.star = alpha[i] + sum(x)
beta.star = beta[i] + n
prior = dgamma(grid,alpha[i],beta[i])
post = dgamma(grid,alpha.star,beta.star)
lines(grid,post,lwd=2)
lines(grid,prior,col=colors[i],lwd=2)
legend("topright",c("Prior","Posterior"),col=c(colors[i],"black"),lwd=2)
}
beginner statistics r
beginner statistics r
asked 22 mins ago
MichelleMichelle
231112
asked 22 mins ago
MichelleMichelle
231112
asked 22 mins ago
MichelleMichelle
231112
asked 22 mins ago
MichelleMichelle
231112
asked 22 mins ago
MichelleMichelle
231112
231112
add a comment |
add a comment |
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