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 2 mins ago
MichelleMichelle
227112
$endgroup$
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 2 mins ago
MichelleMichelle
227112
$endgroup$
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 2 mins ago
MichelleMichelle
227112
$endgroup$
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 2 mins ago
MichelleMichelle
227112
asked 2 mins ago
MichelleMichelle
227112
asked 2 mins ago
MichelleMichelle
227112
asked 2 mins ago
MichelleMichelle
227112
asked 2 mins ago
MichelleMichelle
227112
227112
add a comment |
add a comment |
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