MATLAB Code Implementation for Gaussian Curve Fitting
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Gaussian curve fitting and trend removal are common procedures for analyzing general non-stationary sequences. This process helps us better understand trends and patterns within the sequence. In Gaussian curve fitting, we can employ the least squares method to identify the curve that best fits the dataset, typically implemented using MATLAB's optimization functions like lsqcurvefit or custom fitting algorithms with Gaussian basis functions. Subsequently, we can apply various technical methods to eliminate trends in the sequence, such as differencing techniques (using the diff function) or decomposition methods (like seasonal-trend decomposition). Through these steps, we can more accurately analyze and interpret data within the sequence, providing valuable information for research purposes. Key implementation considerations include parameter initialization for Gaussian models and selection of appropriate detrending methods based on sequence characteristics.
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