Title: GitHub - simiden/RegressionAnalysisR: This was the second in the series of projects completed while taking a class on Data Intensive Computing(CSE 587). The project analyses NYSE data for over a period of 3 years and then calculates the MAE (Mean Absolute Error) to evaluate error in time series analysis. Based on this error, three statistical methods were used to find stocks with best-forecasted performance. The 3 models of prediction used are Arima, Holt-Winters and Linear Regression.
Open Graph Title: GitHub - simiden/RegressionAnalysisR: This was the second in the series of projects completed while taking a class on Data Intensive Computing(CSE 587). The project analyses NYSE data for over a period of 3 years and then calculates the MAE (Mean Absolute Error) to evaluate error in time series analysis. Based on this error, three statistical methods were used to find stocks with best-forecasted performance. The 3 models of prediction used are Arima, Holt-Winters and Linear Regression.
X Title: GitHub - simiden/RegressionAnalysisR: This was the second in the series of projects completed while taking a class on Data Intensive Computing(CSE 587). The project analyses NYSE data for over a period of 3 years and then calculates the MAE (Mean Absolute Error) to evaluate error in time series analysis. Based on this error, three statistical methods were used to find stocks with best-forecasted performance. The 3 models of prediction used are Arima, Holt-Winters and Linear Regression.
Description: This was the second in the series of projects completed while taking a class on Data Intensive Computing(CSE 587). The project analyses NYSE data for over a period of 3 years and then calculates the MAE (Mean Absolute Error) to evaluate error in time series analysis. Based on this error, three statistical methods were used to find stocks with best-forecasted performance. The 3 models of prediction used are Arima, Holt-Winters and Linear Regression. - GitHub - simiden/RegressionAnalysisR: This was the second in the series of projects completed while taking a class on Data Intensive Computing(CSE 587). The project analyses NYSE data for over a period of 3 years and then calculates the MAE (Mean Absolute Error) to evaluate error in time series analysis. Based on this error, three statistical methods were used to find stocks with best-forecasted performance. The 3 models of prediction used are Arima, Holt-Winters and Linear Regression.
Open Graph Description: This was the second in the series of projects completed while taking a class on Data Intensive Computing(CSE 587). The project analyses NYSE data for over a period of 3 years and then calculates th...
X Description: This was the second in the series of projects completed while taking a class on Data Intensive Computing(CSE 587). The project analyses NYSE data for over a period of 3 years and then calculates th...
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