Linked Questions

We have a series of monthly data for 20 months (it is not possible to obtain more data). These are the number of medical consultations encoded in a public hospital and we only have monthly data for ...

I recently got to work on a problem of forecasting five years of data. But I only had five data point from previous years i.e. yearly data (frequency = 1). The data is heteroskedastic. For example, [...

I think this is a basic question but really I just need a definite starting point. I am working in R. I have a dataset as follows ...

I need help to predict future values for a time series (26 observations of consumer prices). This time series is not stationary (i.e I have increasing values of price). What is the best method ...

I would like to forecast for next 2 months using 1 year data captured at monthly level. sample of the data 201702 7 201703 1344 201704 1311 201705 2645 201706 8581 201707 7271 201708 11550 ...

I remember sitting in stats courses as an undergrad hearing about why extrapolation was a bad idea. Furthermore, there are a variety of sources online which comment on this. There's also a mention of ...

I recently applied a range of forecasting methods (MEAN, RWF, ETS, ARIMA and MLPs) and found that MEAN did surprisingly well. (MEAN: where all future predictions are predicted as been equal to the ...

Here is some context. I am interested in determining how two environmental variables (temperature, nutrient levels) impact the mean value of a response variable over a 11 year period. Within each year,...

I have data set comprising 24 rows of monthly data. The features are GDP, airport arrivals, month, and a few others. The dependent variable is number of visitors to a popular tourism destination. ...

I have a set of predictor variables and a target variable. I am really confused with regards to what method to use for forecasting the target variable. For example, my data set has monthly customer ...

I'm working with mixed model for forecasting analysis. One of the decision that we want to take for the modeling is length of time-series, whether it should be 2 years or three years. So my question ...

I have a time series without significant autocorrelation. http://pastebin.com/xZJnZs7k Autocorrelation plot. Partial autocorrelation plot. Here you can find a year worth of data and a forecast ...

I have a time series about demand of a product with many zeros. I was reading the forecasting book by Hyndman and Athanasopoulos [1] (section 2.3), which mentioned the average method for forecasting ...

I got an interview question: Providing 1 year monthly data (12 points), can be traffic, product consumption, etc. How to forecast next month? I am confused. This question doesn't looks like a time ...

I tried auto.arima on my time series and the results converge to mean. Why does this happen? What can I do to correct the error in modelling? Here is my time ...