XLSTAT is using the most commonly found writing, used by most softwares. The differences concern most of the time the sign of the coefficients. The mathematical writing of the ARIMA models differs from one author to the other. They are adapted specifically for time series data more than a classical linear regression model. The models of the ARIMA family allow to represent in a synthetic way phenomena that vary with time, and to predict future values with a confidence interval around the predictions. These models can be used in applied machine learning in various fields such as finance, to predict the evolution of stock price, but also in meteorology to predict temperatures. XLSTAT offers a wide selection of ARIMA models such as ARMA (Autoregressive Moving Average), ARIMA (Autoregressive Integrated Moving Average) or SARIMA (Seasonal Autoregressive Integrated Moving Average). This way, you can easily run an ARIMA for time series forecasting without python or R.
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