Dear Reader,
I’m having trouble with implementing a regression.
I have the following:
I have a 3D matrix results_demands(24,1,n) and a 3D matrix results_han(24,3,n)
Where 24 are the time steps and n are the observations.
I want to model the regression between the (24,1) vector results_demands and (24,3) matrix results_han
What I already tried is splitting up the results_han such that I have a matrix with n rows(observations) and 3 columns and every input is a (24,1) vector.
So that we have 3 response variables and 1 explanatory variable(results_demands) all variables in form of a vector.
How do I need to implement such extra dimensional case.
A visualization of the 3D matrices.
results_han : (24,3,n):
[ [vec_i] [vec_i] [vec_i]
[vec_i] [vec_i] [vec_i]
………………….
…………………. ]
with vec_i a (24,1) column vector
results_demands: (24,1,n):
[ [vec_k]
[vec_k]
……….]
with vec_k a (24,1) column vector
Thank you in advance!Dear Reader,
I’m having trouble with implementing a regression.
I have the following:
I have a 3D matrix results_demands(24,1,n) and a 3D matrix results_han(24,3,n)
Where 24 are the time steps and n are the observations.
I want to model the regression between the (24,1) vector results_demands and (24,3) matrix results_han
What I already tried is splitting up the results_han such that I have a matrix with n rows(observations) and 3 columns and every input is a (24,1) vector.
So that we have 3 response variables and 1 explanatory variable(results_demands) all variables in form of a vector.
How do I need to implement such extra dimensional case.
A visualization of the 3D matrices.
results_han : (24,3,n):
[ [vec_i] [vec_i] [vec_i]
[vec_i] [vec_i] [vec_i]
………………….
…………………. ]
with vec_i a (24,1) column vector
results_demands: (24,1,n):
[ [vec_k]
[vec_k]
……….]
with vec_k a (24,1) column vector
Thank you in advance! Dear Reader,
I’m having trouble with implementing a regression.
I have the following:
I have a 3D matrix results_demands(24,1,n) and a 3D matrix results_han(24,3,n)
Where 24 are the time steps and n are the observations.
I want to model the regression between the (24,1) vector results_demands and (24,3) matrix results_han
What I already tried is splitting up the results_han such that I have a matrix with n rows(observations) and 3 columns and every input is a (24,1) vector.
So that we have 3 response variables and 1 explanatory variable(results_demands) all variables in form of a vector.
How do I need to implement such extra dimensional case.
A visualization of the 3D matrices.
results_han : (24,3,n):
[ [vec_i] [vec_i] [vec_i]
[vec_i] [vec_i] [vec_i]
………………….
…………………. ]
with vec_i a (24,1) column vector
results_demands: (24,1,n):
[ [vec_k]
[vec_k]
……….]
with vec_k a (24,1) column vector
Thank you in advance! multivariate regression, regression, mvregress MATLAB Answers — New Questions

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