# Questions tagged [forecasting]

Prediction of the future events. It is a special case of [prediction], in the context of [time-series].

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### Why does stl() decomposition require integer frequency?

I need to decompose and forecast weekly series with around 10 years of data. In this data leap years play an important role so I need the have non-integer frequency, frequency = (365.25/7) By reading ...
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### Are there any rules of thumb for the number of hidden layer neurons in a RNN or LSTM for time series prediction?

Say that I have a univariate time series X(t) that I want to forecast using RNN/LSTM. I have 2 years of weekly sales data that is seasonal. How many hidden layers and neurons in each layer do I need ...
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### Why is MASE scaled by the mean absolute error produced by a naive forecast calculated on the in-sample data

Wouldn't a better scaling factor be with the MAE produced by a naive forecast on the test data itself? When evaluating MASE for the training set, this essentially becomes a comparison for the ...
399 views

### SAS: Holt Winters Forecasting

If I have an estimate for Holt Winters model as the attached image. How do I interpret the estimates i.e the level, trend and seasonal smoothing weight.
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### Looking ahead at seasonality in time series modeling without overfitting

In forecasting the performance of many agents in a time series, there is a strong seasonality component, in addition to non-seasonal features for each agent. How can I capture the overall seasonal ...
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### Autocorrelation function and forecast in ARIMA model

Let $B$ the lag operator and $\{y_t\}$ the following model $$(1-0.6B^4)y_t=(1+0.2B)\epsilon_t$$ where $\epsilon_t\sim N(0,16)$. a) Is it a stationary process? b) Find the autocorrelation ...
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### When will YTD hit a goal?

I'm estimating a deadline, when my time series will add up (total so far) to a certain large number. I'm doing so by getting a forecast line, plus or minus the RMS error of the known values. But if I ...
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### How to determine or diagnose that time series data contain seasonality pattern for SARIMA in R by function

I want to ask about seasonal ARIMA (SARIMA) in R function how to determine that time series data has affected or influenced by seasonal pattern Thank you very much
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### What model should I use for retirement forecasting?

I am a HR professional looking to self learn statistical modeling for new responsibilities at work. I need to forecast no. of employees who may retire next 10 years. What would be simple way to ...
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### building and analyzing a regression model

I'm trying build a model to predict sells of clothe store for each cluster to month 11 and 12. I've 98 stores, and for each store i have this data, but i put the all data to calc only 1 model. I use ...
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### How to compare the forecast accuracy of two models when the data has unbalanced panel structure?

I am comparing the earnings forecast accuracy of two models (model 1 and model 2). The data (firm-year level data) have an unbalanced panel structure since firms have varying lifetime and time to be ...
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### Constructing a forecast from bayesian multivariable regression

I've been working my way through Kruschke's Doing Bayesian Data Analysis, and have been able to successfully run a Bayesian multivariable regression using R code provided with the book. Kruschke's ...
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### Transforming time series data before change point analysis in R

I have count data (non-financial) from 2010-2014 by week. I am interested in using R and changepoint package to find any significant points of time when the trend changed. I have two questions about ...
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### What is the maximum time series data required for ARIMA and ANN modelling?

I have a per hour data in 1 year for a total of 8,640 observations. These data will be used to model ARIMA and ANN to predict a day-ahead forecast. My question is, is these data enough? or too much?
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### Can simple exponential forecasting be used for a non stationary series?

I have a non stationary series with trend and seasonal components. I want to use simple exponential smoothing ONLY for forecasting. Does the series need to converted to stationary before using SES? If ...
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### Why is the propriety of a scoring rule irrelevant for deterministic forecasts?

By deterministic forecasts Jolliffe (2008) has in mind forecasts to which no representation of uncertainty is attached. Jolliffe (2008) p26 provides a standard explanation of proper scoring rules, ...
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### Calculating prediction interval on differentiated VAR(2)

I want to calculate the $l$ step ahead prediction interval of an VAR(2) on three series. Theses series are differentiated once before estimation of the VAR(2) model. I use the functions of the ...
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### Poor electrical load forecasts from auto.arima, why?

I have 4 years electrical load data. I split the data into 3 years (75%) training data, 1 year for testing (25%). Also I have the temperature data for each day during the previous period. (The link to ...
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### Forecasting seasonal components in X-13ARIMA-SEATS

Forecasting seasonal components is an important practical problem in finance, where products that are highly exposed to monthly seasonality in consumer prices are traded. For example, one can trade ...
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### How to predict the risk of an event?

I'm working on a medical problem, where I want to analyze the effect of taking cholesterol medications on the occurrence of heart attack. Once a medication with a specific dosage is prescribed, it'll ...
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### Forecasting multivariate time series data stream

I have a multivariate time series data stream. I am looking for a method that can forecast the next value of one of the variables as the data comes in. (It would be a major advantage if there's an R ...
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### Time series cross-validation, calculate RMSE for different forecasting horizions

Following Rob J. Hyndman suggestions on how to do cross validation for time series ( http://robjhyndman.com/hyndsight/tscvexample/ ), I modified his original code to evaluate how RMSE (not MAE) ...
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### Dynamic regression linear models in R

I have a question regarding Dynamic regression linear models. I wonder if it is possible to implement a MLR model (in R) using 'lm' and creating lagged values of predictors and dependent variables. ...
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### How to improve a bad long-term forecasting of time series in common case

I have two time series $d_t(t)$, $d_c(t)$, where I'm modelling charge as a function of time. Lengths of time series, $N$ are equal to $101$ data points. For the $d_t(t)$ (test sample, short-term) the ...
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### How to detect a relatively small level shift(leakage) in an hourly water flux time series in an area?

Background I'm working on a project which aims to use the history data about a water flux to detect whether there is a leakage happened. The data is hourly collected and among about 4 months. I've ...
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### Predict (un)employment variables - very small dataset

I'm new to econometrics (familiar with ML, Python, Data Visualization). I really have no clear idea what model should I use in order to predict (un)employment variables for 2015-2016 (potentially 2020,...
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### ARMA-GARCH forecast evaluation: in-sample, out-of-sample, rolling

I need to compare the forecasting ability of different specifications of the ARMA-GARCH model. I would like to compare the model by valuating for each model in-sample forecast and out-of-sample ...
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### Predicting Influence of Price on Sales with Limited Stock

I'm trying to develop a model that predicts the volume of sales (either incremental for each day, or total at the end of a period) that factors in price, but I'm having some trouble working around ...
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### Determining forecast error of realtime prediction of binary outcomes

Given datasets consisting of a daily prediction and confidence percentage for each of a small number of binary outcomes, what is the proper way to calculate the forecast error of each series and of ...
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### Variance on Extreme Seasonal Time Series

I'm trying to come up with a decent method for forecasting a unique seasonal time series that is involving multiple periods of seasonality: Weekly, Monthly, Quarterly and I am stuck because I have ...