I have a Matlab code that calculates average yearly sunspot numbers in America from 1947-2016. I need someone to add an extension to my code to create an accurate regression model of these data points i.e. (least squares, nonlinear regression, autoregressive, etc) that can also be used for forecasting future sunspot numbers. The one you chose should be based on goodness of fit and minimizing error. The error in the fit should be calculated and printed. Outlier points in the data set can be ignored to make the fit better. But these points should be indicated on the graph produced still and should be kept to only a few. The second part of this is based on forecasting what the next 100 years of avg yearly sunspot numbers would look like. This should be on a second graph and look similar to the attached image in this file. Please make sure to heavily comment your work so a beginner programmer can understand your techniques used and not to use any regression models that are too complex for a beginner.
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I have worked with regression models in MATLAB multiple times in the past. I have checked your project description and I believe I can get the job done for you!
Hi. I am a mathematician and a statistician. I have many experiences in ML such as regression... I am sure I can help you. We can discuss details via chat. I wait for you now. Thanks.
Hello! Do you machine learning? There are powerful machine learning models for prediction of time series: ARIMA model and some deep learning models (MLP & RNN). Thanks.
I am PhD scholar working in area of prediction of time series data. I use Neural Network, Fuzzy based prediction. Regression analysis , I can do easily. I can do this work with reasonable accuracy.