Bayesian vector autoregression, forecasting
danilamaroz / bvar.jl Goto Github PK
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Bayesian vector autoregression, forecasting
XXX = Array(Float64, 5)
for i in 1:30
XXX[i] = zeros(Float64, 4)
end
What could be the alternative of c() from R in Julia?
For now i figured out using vec() when needed to be vectorized and then unite the results using [a ; b]
so it looks something like [vec(X); vec(Y); 1]. Fine like that?
Constantly running into the conversion issue, when trying to assign an array of higher dimension to a lower dimensional object.
e.g. the following gives error
x = zeros(5)
x[1] = ones(1, 1)
is there a better way, instead of extracting the singleton
x[1] = ones(1, 1)[1, 1]
or reshaping in case of higher dimensions?
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