How to fit time series to the curve-linear trend
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Hi,
I have fluctuating data with its own curve-linear trend(2) and by polynomial fitting I got curve-linear trend(1). How can I fit fluctuating data(2) to the curve-linear trend(1), so that data are extended by symetric reflection or any kind of data extension?
Like in the figure below.
(Thank you Adam Danz)
![untitled1_c.png](https://www.mathworks.com/matlabcentral/answers/uploaded_files/201393/untitled1_c.png)
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Adam Danz
am 24 Jan. 2019
Bearbeitet: Adam Danz
am 24 Jan. 2019
Since your data look approximately normally distributed, you can measure the standard deviation of your data and use that to produce random numbers from a normal distrubution with a mean of your trendline. Here's general instructions.
Step 1: standardize your data by subtracting the mean (which is the trend line): dataStandard = data - trendline
Step 2: calcuate the standard deviation of the standardized data: sd = std(dataStandard)
Step 3: produce random-normal noise with standard deviation calucated in step 2 and the mean will be your red trend line.: newData = normrnd(0, sd, 1, length(trendline)) + trendline.
Step 4: plot the new data: plot(trendline, newData)
4 Kommentare
Adam Danz
am 25 Jan. 2019
To clarify my solution (which seems like it would work in your explanation above),
dataStandard = data - trendlineBlue;
new_data = dataStandard + trendlineRed;
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