Forecasting involves estimating values (or distributions) that have not yet been observed.
I am trying to forecast a yearly time series on a weekly bases (52 weeks a year and I have 164 weeks …
r forecasting state-spaceI'm working on a multivariate (100+ variables) multi-step (t1 to t30) forecasting problem where the time series frequency is every 1 minute. …
python machine-learning time-series forecasting facebook-prophetI'm generating an Arima model with an external regressor. Let's suppose I have n observations. The predict.Arima function from …
r forecasting predictI was analyzing some geographical data and attempting to predict/forecast next occurrence of event with respect to time and …
python numpy machine-learning scikit-learn forecastingI found a site which explains exactly what I need to do for my data however it isn't in R. …
r forecastingI know that MAPE and WMAPE as a forecast error metrics, they have some benefits. But what's the gaps? Someone …
machine-learning forecastingUnable to find forecast.Arima function in forecast package. Error displayed "forecast.Arima" not found. Can forecast function be used …
forecasting arimaI'm using statsmodels.tsa.SARIMAX() to train a model with exogenous variables. Is there an equivalent of get_prediction() when …
python time-series forecasting statsmodels confidence-intervalI have a .csv file containing a 5-year time series, with hourly resolution (commoditiy price). Based on the historical data, …
python forecasting statsmodelsI'm a newbie to R, coming from the Stata world. I've just run a linear model (with approx 100 variables, each …
r stata linear-regression forecasting standard-error