MATLAB: Data frequency conversion problem

data

Dear all,
Is there any function for converting data that are available every 2 months to monthly data
thank you
EDIT [01 Aug 2012, 19:33 BST – OK] Added example input from comment
Here is an example of a panel data set with 3 individuals
A = {
    1    '1-2 2004'      0.256       0.385
    1    '3-4 2004'      0.268      3.0394
    1    '5-6 2004'     0.0504      0.6475
    1    '7-8 2004'    14.0985    148.2583
    1    '9-10 2004'     0.1128      1.1506
    1    '11-12 2004'        NaN    148.2583
    1    '1-2 2005'        NaN    148.2583
    1    '3-4 2005'     2.5852     34.0146
    1    '5-6 2005'      0.322      3.2846
    1    '7-8 2005'    14.0985    148.2583
    1    '9-10 2005'     2.5852         NaN
    1    '11-12 2005'     0.2938       2.854
    2    '1-2 2004'      0.256       0.385
    2    '3-4 2004'      0.268      3.0394
    2    '5-6 2004'     0.0504      0.6475
    2    '7-8 2004'    14.0985    148.2583
    2    '9-10 2004'     0.1128      1.1506
    2    '11-12 2004'        NaN    148.2583
    2    '1-2 2005'        NaN    148.2583
    2    '3-4 2005'     2.5852     34.0146
    2    '5-6 2005'      0.322      3.2846
    2    '7-8 2005'    14.0985    148.2583
    2    '9-10 2005'     2.5852         NaN
    2    '11-12 2005'     0.2938       2.854
    3    '1-2 2004'      0.256       0.385
    3   '3-4 2004'      0.268      3.0394
    3    '5-6 2004'     0.0504      0.6475
    3    '7-8 2004'    14.0985    148.2583
    3    '9-10 2004'     0.1128      1.1506
    3    '11-12 2004'        NaN    148.2583
    3    '1-2 2005'        NaN    148.2583
    3    '3-4 2005'     2.5852     34.0146
    3    '5-6 2005'      0.322      3.2846
    3    '7-8 2005'    14.0985    148.2583
    3    '9-10 2005'     2.5852         NaN
    3    '11-12 2005'     0.2938       2.854}
Note that I have 30000 invividuals (instead of 3) and 20 numerical columns instead of the last 2 that I display above. The interpolation should be done for each i=1,2,3 separately.

Best Answer

EDIT#2 I didn't notice at first that it had different series. Added also linear interpolation of NaNs:
% Inpaint NaNs and keep numeric matrix (easier to work than with cell % arrays) with inpaint_nans() from the FEX.
data       = inpaint_nans(cell2mat(A(:,3:4)),2);
% Partition interpolation in blocks (first column)
blocks     = [A{:,1}];
unBlocks   = unique(blocks);
% Preallocate
interpData = cell(numel(unBlocks),1);
% Interpolate each block
for b = unBlocks
    idxBlock      = b == blocks;      % index the block
    n             = nnz(idxBlock)*2;  % counts its length
    interpData{b} = interp1((1:2:n)', data(idxBlock,:),(1:n-1)');
end
% This plot gives an idea of the type of interpolation (for the first block/series only)
subplot(311)
plot(1:2:n,[A{1:15,3}],'-or')
legend('original')
subplot(312)
plot(1:n-1,interpData{1}(:,1)','-db')
legend('linear interp')
subplot(313)
plot(1:2:n,[A{1:15,3}],'-or',1:n-1,interpData{1}(:,1)','-db')
As you can see, you need to decide what to do with NaN's (especially to avoid losing info)
% Concatenate the cells into one numeric matrix (optional)
interpData = cat(1,interpData{:});
WARNING: with this approach I assume every month has same length.
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