Error of Index exceeds matrix dimensions. Please help

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oluwatayo ogunmiloro
评论： oluwatayo ogunmiloro 2020-4-22
% 2016 2017 2018 2019
y = [3 2 6 6 % Jan
6 1 10 9 % Feb
2 5 4 0 % Mar
1 7 5 3 % Apr
0 1 0 8 % May
0 3 4 1 % Jun
0 5 7 1 % Jul
2 0 4 0 % Aug
3 2 1 6 % Sep
2 5 3 4 % Oct
1 1 1 4 % Nov
3 2 5 2 ]; % Dec
% Source:personal library
yr = repmat((2016:2019),12,1);
mo = repmat((1:12)',1,12);
time = datestr(datenum(yr(2016:2019),mo(1:12),1));
ts = timeseries(y(:),time,'name','Diabetes Diagnosis in Male Individuals');
ts.TimeInfo.Format = 'dd-mmm-yyyy';
tscol = tscollection(ts);
plot(ts)
%Examine Trend and Seasonality
%This series seems to have a strong seasonal component, with a trend that may be linear
%or quadratic. Furthermore, the magnitude of the seasonal variation increases as
%the general level increases. Perhaps a log transformation would make the seasonal
%variation be more constant. First we'll change the axis scale.
h_gca = gca;
h_gca.YScale = 'log';
%It appears that it would be easier to model the seasonal component on the log scale.
%We'll create a new time series with a log transformation.
tscol = addts(tscol,log(ts.data),'logdiabetes complications');
logts = tscol.logAirlinePassengers;
%Now let's plot the yearly averages, with monthly deviations superimposed.
%We want to see if the month-to-month variation within years appears constant.
%For these manipulations treating the data as a matrix in a month-by-year format,
%it's more convenient to operate on the original data matrix.
t = reshape(datenum(time),12,12);
logy = log(y);
ymean = repmat(mean(logy),12,1);
ydiff = logy - ymean;
x = yr + (mo-1)/12;
plot(x,ymean,'b-',x,ymean+ydiff,'r-')
title('Monthly variation within year')
xlabel('Year')
%Now let's reverse the years and months, and try to see if the year-to-year trend
%is constant for each month.
subplot(1,1,1);
X = [dummyvar(mo(:)) logts.time];
[b,bint,resid] = regress(logts.data,X);
tscol = addts(tscol,X*b,'Fit1')
%Time Series Collection Object: unnamed
%Time vector characteristics
% Start date 01-Jan-2016
% End date 01-Dec-2019
%Member Time Series Objects:
% Diabetes diagnosis
% logDiabetes diagnosis
% Fit1
plot(logts)
hold on
plot(tscol.Fit1,'Color','r')
hold off
legend('Data','Fit','location','NW')
%Based on this graph, the fit appears to be good. The differences between the actual
%data and the fitted values may well be small enough for our purposes.
%But let's try to investigate this some more. We would like the residuals to look
%independent. If there is autocorrelation (correlation between adjacent residuals),
%then there may be an opportunity to model that and make our fit better. Let's create
%a time series from the residuals and plot it
tscol = addts(tscol,resid,'Resid1');
plot(tscol.Resid1)

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采纳的回答

David Welling
David Welling 2020-4-21
in line 17 ( time = datestr(datenum(yr(2016:2019),mo(1:12),1)); ), You call array yr(2016:2019). the size of the array is however, 12x4. the index of yr in this line is incorrect. it also has only one dimension, not two.
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Walter Roberson
Walter Roberson 2020-4-22
You appear to be adding a timeseries named 'logdiabetes complications' but then trying to access a timeseries named 'logdiabetes'
oluwatayo ogunmiloro
oluwatayo ogunmiloro 2020-4-22
@Walter Roberson. Great one from you! I have actually corrected that and it works. However i encountered another error in line 37. I have altered the datenum(time) from 12, 12 to 12, 4, 4, 12 and so on but it still not working. Thanks for your effiort. I eagerly await your kind answers.
Error in Untitled4 (line 37)
t = reshape(datenum(time),12,12);

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