Adjoint vs row vector

General Usage
1

If I want to represent a time series as row vector, can I just represent it as adjoint?

Or should I represent it as 1xn matrix?

julia> u=[1,2,3]'
1×3 adjoint(::Vector{Int64}) with eltype Int64:
 1  2  3

julia> [1 2 3]
1×3 Matrix{Int64}:
 1  2  3

julia> v=[1 2 3]
1×3 Matrix{Int64}:
 1  2  3
2

I guess this depends on your use case?

Normally when people say “time series” they mean some sort of container where each element has a time stamp associated with it, e.g. the TimeArray in the TimeSeries package. You just have a plain vector and whether there are meaningful differences between using an adjoint or a 1xn matrix likely depends on your application.

3

Why a row vector as such? A vector is inherently 1D, not either column or row. Even though in the context of linear algebra we tend to use them as though they were columns, it doesn’t have to be that way.