117 lines
2.6 KiB
Matlab
117 lines
2.6 KiB
Matlab
%% This function was automatically generated. When modifying its signature, take care to apply
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%% modifications also to the descriptor files in the repository.
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%% function out = my_app(Time Series File, Number of lags , Number of standard deviations)
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function [acf,lags,bounds,numLags,numMA,numSTD] = ...
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autocorr(time_series,numLags,numMA,numSTD)
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[rows,columns] = size(time_series);
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if (rows ~= 1) && (columns ~= 1)
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error('Input file must be a vector');
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end
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time_series = time_series(:); % Ensure a column vector
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N = length(time_series); % Sample size
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defaultLags = 20; % Recommendation of [1]
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% Ensure numLags is a positive integer or set default:
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if (nargin >= 2) && ~isempty(numLags)
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if numel(numLags) > 1
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error('Number of lags must be a scalar value');
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end
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if (round(numLags) ~= numLags) || (numLags <= 0)
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error('Number of lags must be a positive integer');
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end
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if numLags > (N-1)
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error('Number of ACF lags must not exceed the number of observations minus one');
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% numLags = min(defaultLags,N-1)
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end
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else
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numLags = min(defaultLags,N-1); % Default
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end
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% Ensure numMA is a nonnegative integer or set default:
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if (nargin >= 3) && ~isempty(numMA)
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if numel(numMA) > 1
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error('Number of moving average must be a scalar value');
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end
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if (round(numMA) ~= numMA) || (numMA < 0)
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error('Number of moving average must be a positive integer');
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end
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if numMA >= numLags
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error('Number of moving average must be lower than number of lags');
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end
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else
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numMA = 0; % Default
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end
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% Ensure numSTD is a positive scalar or set default:
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if (nargin >= 4) && ~isempty(numSTD)
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if numel(numSTD) > 1
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error('Number of standard deviations must be a scalar value');
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end
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if numSTD < 0
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error('Number of standard deviations cannot be negative');
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end
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else
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numSTD = 2; % Default
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end
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nFFT = 2^(nextpow2(length(time_series))+1);
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F = fft(time_series-mean(time_series),nFFT);
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F = F.*conj(F);
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acf = ifft(F);
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acf = acf(1:(numLags+1)); % Retain non-negative lags
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acf = acf./acf(1); % Normalize
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acf = real(acf);
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% Compute approximate confidence bounds using the approach in [1],
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% equations 2.1.13 and 6.2.2, pp. 33 and 188, respectively:
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sigmaNMA = sqrt((1+2*(acf(2:numMA+1)'*acf(2:numMA+1)))/N);
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bounds = sigmaNMA*[numSTD;-numSTD];
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lags = (0:numLags)';
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end |