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tarek Jan liked Bohdan Pavlyshenko's blog post Linear, Machine Learning and Probabilistic Approaches for Time Series AnalysisPosted on March 8, 2018 at 9:00am 2 Comments 5 Likes
Sales prediction is an important part of modern business intelligence. First approaches one can apply to predict sales time series are such conventional methods of forecasting as ARIMA and Holt-Winters. But there are several challenges while using these methods. They are: multilevel daily/weekly/monthly/yearly seasonality, many exogenous factors which impact sales, complex trends in different time periods. In such cases, it is not easy to apply conventional methods. Of course, there is…
ContinuePosted on October 26, 2017 at 11:30pm 0 Comments 1 Like
One of the main goals in the Bitcoin analytics is price forecasting. There are many factors which influence the price dynamics. The most important factors are: the interaction between supply and demand, attractiveness for investors, financial and macroeconomics indicators, technical indicators such as difficulty, how many blocks were created recently, etc. A very important impact on the cryptocurrency price has trends…
Posted on February 26, 2017 at 5:30am 2 Comments 10 Likes
In this post, we consider different approaches for time series modeling. The forecasting approaches using linear models, ARIMA alpgorithm, XGBoost machine learning algorithm are described. Results of different model combinations are shown. For probabilistic modeling the approaches using copulas and Bayesian inference are considered.
INTRODUCTION
Time series analysis, especially forecasting, is an important problem of modern…
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