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matlabaveragemeanaccumarray

MATLAB Accumarray weighted mean


So I am currently using 'accumarray' to find the averages of a range of numbers wich correspond to matching ID's. Ex Input:

ID----Value
1     215
1     336
1     123
2     111
2     246
2     851

My current code finds the unweighted average of the above values, using the ID as the 'seperator' so that I don't get the average for all of the values together as one number, but rather seperate results for just values which have corresponding ID's. EX Output:

ID----Value
1     224.66
2     402.66

To achieve this I am using this code:

[ID, ~, Groups] = unique(StarData2(:,1),'stable');
app = accumarray(Groups, StarData2(:,2), [], @mean);

With StarData2 being the input of the function. This is working perfectly for my purposes until now, I need to know if accumarray can be made to give me a weighted average, such that each point in app (before the average is found) can be assigned a weight or that the @mean can be replaced with a function that can achieve this. The new input will look like this:

ID----Value----Weight
1     215     12
1     336     17
1     123     11
2     111     6
2     246     20
2     851     18

The new code must do the sum(val(i)*weight(i))/sum(weight) instead of just the standard mean. Thanks for any assistance.


Solution

  • You can use the row index as the "vals" (second input to accumarray) and define your own function that does the weighted mean on group of the data:

    Weights = data(:,3); Vals = data(:,2); % pick your columns here
    WeightedMeanFcn = @(ii) sum(Vals(ii).*Weights(ii))/sum(Weights(ii));
    wmeans = accumarray(Groups, 1:numel(Groups), [], WeightedMeanFcn)
    

    Demonstration

    Starting with data (the new input with your weights) and your unique command:

    data = [1,215,12; 1,336,17; 1,123,11; 2,111,6; 2,246,20; 2,851,18];
    [ID, ~, Groups] = unique(data(:,1),'stable');
    

    The accumarray usage is as follows (redefine WeightedMeanFcn every time you change data!):

    >> Weights = data(:,3); Vals = data(:,2); % pick your columns here
    >> WeightedMeanFcn = @(ii) sum(Vals(ii).*Weights(ii))/sum(Weights(ii));
    >> app = accumarray(Groups, 1:numel(Groups), [], WeightedMeanFcn)
    app =
      241.1250
      475.0909
    

    Checking manually, with the first group:

    ig = 1;
    sum(data(Groups==ig,2).*data(Groups==ig,3))/sum(data(Groups==ig,3))
    ans =
      241.1250