I gave a look at SAS and honestly I don't understand how they got those values!
My approach was to take intra-month averages (I tried to interpret SASs method) and then interpolate them:
A = {
1 '13JAN1992' 55
2 '27JAN1992' 73
3 '19FEB1992' 84
4 '08MAR1992' 69
5 '27MAR1992' 66
6 '05APR1992' 77
7 '29APR1992' 63
8 '11MAY1992' 81
9 '25MAY1992' 89
10 '07JUN1992' 94
11 '23JUN1992' 105
12 '11JUL1992' 97
13 '15AUG1992' 112
14 '29AUG1992' 89
15 '10SEP1992' 77
16 '27SEP1992' 82}
% Convert dates to serial dates and store with data in a double matrix
data = [datenum(A(:,2),'ddmmmyyyy') cat(1,A{:,3})];
% Retrieve month year day
[yy mm dd] = datevec(data(:,1));
% Create aggregation subs for accumarray
subsr = repmat((yy-yy(1))*12 + mm-mm(1) + 1,2,1);
subsc = repmat(1:size(data,2),size(data,1),1);
% Take averages
avgData = accumarray([subsr subsc(:)], data(:),[],@nanmean);
% Interpolate
xi = datenum(1992,1:9,1);
intData = interp1(avgData(:,1),avgData(:,2),xi,'linear','extrap')
% Also, direct interpolation without averaging
intData2 = interp1(data(:,1),data(:,2),xi,'linear','extrap');
Plot
plot(data(:,1),data(:,2),'-db',xi,intData,'--om',xi,intData2,'-.+r')
axis tight
grid on
set(gca,'Xtick',xi)
datetick('x','mmm yy','keepticks')
legend('your data','interpolation of averages','direct interpolatio','location','NorthWest')
I feel a clarification is needed in response to salva's comments:
I don't know how many times I already said that, but manipulating data is dodgy. Even more the way SAS accomplishes that, which is not CLEAR from the link.
If you're doing research in finance/economics and you manipulate your data because you need it at certain points in time (at the beginning of the month) it's gonna already be an artificial result, but acceptable.
Do you think SAS is fancy because it changes ALL the values, well I assure SASs power isn't that.
MATLAB may lack some functions, but nobody stops you from writing your own and sharing it on the FEX.
MATLAB is not just a program but a programming language and it's not limited to statistics!
So yes, SAS could be more suited for statistical analysis because it has more embedded functions.
