I'm stuck at the following code:
y = c(2.5, 6.0, 6.0, 7.5, 8.0, 8.0, 16.0, 6.0, 5.0, 6.0, 28.0, 5.0, 9.5,
6.0, 4.5, 10.0, 14.0, 3.0, 4.5, 5.5, 3.0, 3.5, 6.0, 2.0, 3.0, 4.0,
6.0, 5.0, 6.5, 5.0, 10.0, 6.0, 18.0, 4.5, 20.0)
x2 = c(650, 2500, 900, 800, 3070, 2866, 7500, 800, 800, 650, 2100, 2000,
2200, 500, 1500, 3000, 2200, 350, 1000, 600, 300, 1500, 2200, 900,
600, 2000, 800, 950, 1750, 500, 4400, 600, 5200, 850, 5000)
x1 = c(16.083, 48.350, 33.650, 45.600, 62.267, 73.2170, 204.617, 36.367,
29.750, 39.7500, 192.667, 43.050, 65.000, 44.133, 26.933, 72.250,
98.417, 78.650, 17.417, 32.567, 15.950, 27.900, 47.633, 17.933,
18.683, 26.217, 34.433, 28.567, 50.500, 20.950, 85.583, 32.3830,
170.250, 28.1000, 159.8330)
library(MASS)
n = length(y)
X = matrix(nrow = n, ncol = 2)
for (i in 1:n) {
X[i,1] = x1[i]
}
for (i in 1:n) {
X[i,2] = x2[i]
}
gibbs = function(data, m01 = 0, m02 = 0, k01 = 0.1, k02 = 0.1,
a0 = 0.1, L0 = 0.1, nburn = 0, ndraw = 5000) {
m0 = c(m01,m02)
C0 = matrix(nrow=2,ncol=2)
C0[1,1] = 1/k01
C0[1,2] = 0
C0[2,1] = 0
C0[2,2] = 1/k02
beta = mvrnorm(1,m0,C0)
omega = rgamma(1,a0,1)/L0
draws = matrix(ncol=3,nrow=ndraw)
it = -nburn
while (it < ndraw) {
it = it + 1
C1 = solve(solve(C0)+omega*t(X)%*%X)
m1 = C1%*%(solve(C0)%*%m0+omega*t(X)%*%y)
beta = mvrnorm(1,m1,C1)
a1 = a0 + n/2
L1 = L0 + t(y-X%*%beta)%*%(y-X%*%beta) / 2
omega = rgamma(1, a1, 1) / L1
if (it > 0) {
draws[it,1] = beta[1]
draws[it,2] = beta[2]
draws[it,3] = omega
}
}
return(draws)
}
When I run it I get :
Error in omega * t(X) %*% X : non-conformable arrays
But when I check omega * t(X) %*% X outside the function I get a result which means that the arrays are conformable,and I have no idea why I'm getting this error. Any help would be much appreciated.
This question is related to
r
The problem is that omega in your case is matrix of dimensions 1 * 1. You should convert it to a vector if you wish to multiply t(X) %*% X by a scalar (that is omega)
In particular, you'll have to replace this line:
omega = rgamma(1,a0,1) / L0
with:
omega = as.vector(rgamma(1,a0,1) / L0)
everywhere in your code. It happens in two places (once inside the loop and once outside). You can substitute as.vector(.) or c(t(.)). Both are equivalent.
Here's the modified code that should work:
gibbs = function(data, m01 = 0, m02 = 0, k01 = 0.1, k02 = 0.1,
a0 = 0.1, L0 = 0.1, nburn = 0, ndraw = 5000) {
m0 = c(m01, m02)
C0 = matrix(nrow = 2, ncol = 2)
C0[1,1] = 1 / k01
C0[1,2] = 0
C0[2,1] = 0
C0[2,2] = 1 / k02
beta = mvrnorm(1,m0,C0)
omega = as.vector(rgamma(1,a0,1) / L0)
draws = matrix(ncol = 3,nrow = ndraw)
it = -nburn
while (it < ndraw) {
it = it + 1
C1 = solve(solve(C0) + omega * t(X) %*% X)
m1 = C1 %*% (solve(C0) %*% m0 + omega * t(X) %*% y)
beta = mvrnorm(1, m1, C1)
a1 = a0 + n / 2
L1 = L0 + t(y - X %*% beta) %*% (y - X %*% beta) / 2
omega = as.vector(rgamma(1, a1, 1) / L1)
if (it > 0) {
draws[it,1] = beta[1]
draws[it,2] = beta[2]
draws[it,3] = omega
}
}
return(draws)
}
Source: Stackoverflow.com