The answer to the original question is yes ! Here is a link to specific Neural prophet documentation with several examples of how to use multivariate inputs.5 Şub 2019
Read moreWhat is DS and Y in Prophet?
The input to Prophet is always a dataframe with two columns: ds and y . The ds (datestamp) column should be of a format expected by Pandas, ideally YYYY-MM-DD for a date or YYYY-MM-DD HH:MM:SS for a timestamp. The y column must be numeric, and represents the measurement we wish to forecast.
Read moreWhat is multi step ahead forecasting?
Multistep-ahead prediction is the task of predicting a sequence of values in a time series . A typical approach, known as multi-stage prediction, is to apply a predictive model step-by-step and use the predicted value of the current time step to determine its value in the next time step.
Read moreWhat is one step ahead forecasting?
One-step ahead forecasts are computed sequentially for each data point by using computed level and trend states for the current point, and seasonal states for the last seasonal period . Forecast error is computed by subtracting forecast value at the previous point from the observed value at the current point.
Read moreWhat is time series forecasting methods?
Time series forecasting occurs when you make scientific predictions based on historical time stamped data . It involves building models through historical analysis and using them to make observations and drive future strategic decision-making.
Read moreWhat is Horizon in time series forecasting?
The forecast horizon is the length of time into the future for which forecasts are to be prepared . These generally vary from short-term forecasting horizons (less than three months) to long-term horizons (more than two years).
Read moreWhat is univariate in time series?
The term “univariate time series” refers to a time series that consists of single (scalar) observations recorded sequentially over equal time increments . … If the data are equi-spaced, the time variable, or index, does not need to be explicitly given.
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