How can I use rmse for two array of different sizes?

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Romero Lacerda 2022-11-8

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编辑： DGM 2023-8-31

I want to do a rmse between one vector 2861x1 and one column of a matrix 6x5761. I tried to do use the rmse by the following example, but the results seems to be much wrong. Is there a better way to do compute the RMSE?

RMSE_tsurf = rmse(tr_s(5,:),t_surf,"all");

RMSE_tmid = rmse(tr_m(5,:),t_mid,"all");

RMSE_tbottom = rmse(tr_b(5,:),t_bottom,"all");

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Jan 2022-11-8

Which one is the "one vector 2861x1"? What does "seems to be much wrong" mean? Before a "better" way can be found, a definition of "god and bad" is required.

DGM 2022-11-8

What is the relationship between a 2861x1 vector and a 6x5761 array? ... or are you only using one column from the 6x5761 array? If so, the same question applies. What is the relationship between the two vectors?

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Answer 1

Raj 2023-8-31

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在 MATLAB Online 中打开

Hi, I understand you are trying to find a rmse of 2 array of different sizes. For doing so, you need to interpolate length of one vector to other to calculate rmse.

Additionally, you can refer to the example below to calculate rmse.

% Example vectors
a = [1, 2, 3, 4, 5];
b = [1.2, 2.3, 3.5, 4.1, 5.2, 6.3, 7.4];
% Determine the minimum size of the vectors
minSize = min(length(a), length(b));
% Trim the vectors to the minimum size
a = a(1:minSize);
b = b(1:minSize);
%c Calculate rmse using rmse function
reqans = rmse(a,b)
reqans = 0.2933

Refer to the documentation link attached below to understand how rmse function works.

https://in.mathworks.com/help/matlab/ref/rmse.html?searchHighlight=rmse&s_tid=srchtitle_support_results_1_rmse#mw_a642ce4c-1a42-4a05-ab62-3019b1231238

I hope this answers your query.

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DGM 2023-8-31

编辑：DGM 2023-8-31

在 MATLAB Online 中打开

If I had this pair of related matrices that I wanted to compare:

Would it make sense to compare the first MxN elements?

Why should we presume that the two vectors should be registered on their first elements?
Why should we truncate the vectors to length instead of interpolating or permuting them?
How does this apply when the inputs aren't both aligned along the same dimension?
How does this apply when the inputs aren't necessarily vectors?
How does this apply when the input lengths aren't integer divisible by each other?
How does this apply when the inputs aren't aligned, aren't vectors, and don't have integer-divisible lengths -- as is the case in the question as asked?

% Example vectors
a = (1:10).'; % a column vector
b = repmat([2;4;6],[1 17]); % a matrix with geometry indivisible by the length of a
% Determine the minimum size of the vectors
minSize = min(length(a), length(b)); % using length() is a great way to create bugs
% Trim the vectors to the minimum size
a = a(1:minSize); % a is a column vector
b = b(1:minSize); % now b is a row vector sampled from the columns of b??
% Calculate rmse using rmse function
ans1 = rmse(a,b) % did you expect the output to be a vector?
ans1 = 1×10
    4.5277    3.2404    2.9155    4.5277    3.2404    2.9155    4.5277    3.2404    2.9155    4.5277
ans2 = rmse(a,b.') % what about?
ans2 = 3.6469
% what do other functions do when you feed them misaligned inputs?
blah = mse(a,b) % that's not the square of either previous answer
blah = 38.5000
blah = atan2d(a,b) % now the output is a matrix
blah = 10×10
   26.5651   14.0362    9.4623   26.5651   14.0362    9.4623   26.5651   14.0362    9.4623   26.5651
   45.0000   26.5651   18.4349   45.0000   26.5651   18.4349   45.0000   26.5651   18.4349   45.0000
   56.3099   36.8699   26.5651   56.3099   36.8699   26.5651   56.3099   36.8699   26.5651   56.3099
   63.4349   45.0000   33.6901   63.4349   45.0000   33.6901   63.4349   45.0000   33.6901   63.4349
   68.1986   51.3402   39.8056   68.1986   51.3402   39.8056   68.1986   51.3402   39.8056   68.1986
   71.5651   56.3099   45.0000   71.5651   56.3099   45.0000   71.5651   56.3099   45.0000   71.5651
   74.0546   60.2551   49.3987   74.0546   60.2551   49.3987   74.0546   60.2551   49.3987   74.0546
   75.9638   63.4349   53.1301   75.9638   63.4349   53.1301   75.9638   63.4349   53.1301   75.9638
   77.4712   66.0375   56.3099   77.4712   66.0375   56.3099   77.4712   66.0375   56.3099   77.4712
   78.6901   68.1986   59.0362   78.6901   68.1986   59.0362   78.6901   68.1986   59.0362   78.6901
blah = immse(a,b) % now the output is an error
Error using immse
A and B must have the same size.

There's a reason this question didn't get answered. It's fine to stretch relevance when answering dead questions, but it's important that a response to an unanswerable question actually acknowledges that the question was flawed. Responding with a solution to the most trivial case without mentioning its limited relevance to the question or its applicability to any similar task makes this seem all the more like AI-generated chaff.

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