# normal error distribution
(D1 <- LMCondDistribution(theta = 1)) # corresponds to Norm(cond, 1)
plot(D1)
r(D1)
d(D1)
p(D1)
q(D1)
## in RStudio or Jupyter IRKernel, use q.l(.)(.) instead of q(.)(.)
param(D1)
cond(D1)
d(D1)(0, cond = 1)
d(Norm(mean=1))(0)
E(D1, cond = 1)
E(D1, function(x){x^2}, cond = 2)
E(Norm(mean=2), function(x){x^2})
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