Questions tagged [forecasting]

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

1,124 questions with no upvoted or accepted answers
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185 views

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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156 views

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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98 views

How is the number of parameters k determined when calculating the AIC of an ARIMA model?

An ARIMA model is specified by 3 parameters $(p,q,d)$ or 6 (+1 for the seasonality) if we consider a seasonal ARIMA model $(p,q,d)(P,Q,D)_s$. The AIC used to select ARIMA models is calculated by: $...
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431 views

Accuracy measures in training/test split of time series

I'm using Forecast Principles and Practice 2 to study time series and a doubt came in mind while I was trying to do exercise 7 of chapter 3. How sensitive are the accuracy measures to the training/...
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62 views

Forecasting costs with forecast interval using past performance

I'm trying to adopt a model for project cost forecasting in agile. Consider the following table of previous costs per sprint, along with story points completed: ...
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267 views

Does there exist a variant of ARIMA allowing for weighted samples?

I have a univariate time series exhibiting strong periodicity that I want to forecast, and I plan to use ARIMA. However due to specifics of the prediction task that I'm interested in performing, some ...
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1answer
113 views

ARIMA forecasting using exogenous variables with their own forecast intervals

Suppose model <- Arima(y , xreg=cbind(x1, x2), order=(p,d,q)) If I am forecasting $x_1$ and $x_2$, then for forecasting $y$: 1) If I use expected forecasts ...
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307 views

Is there any interpretation of parameters in Holt Winters method?

I am doing forecast on time series on R and I use exponential smoothing method Holt Winters. Does a value of $\alpha$ close to $0$ or $1$ "mean" something particular about the series? Same question ...
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88 views

What machine learning techniques to use to predict for multiple seperate sequences of time-series data?

I am having difficulty structuring my data and finding a machine learning technique to predict my outcome. My data: I have a number of users with observations of a number of factors each year, each ...
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306 views

How much do the parameters in the Holt-Winters model matter?

When fitting a Holt-Winters model, I usually take the approach of retrospectively "predicting" some known historical values for the series, and optimising the coefficients for the parameters by ...
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1answer
455 views

A time series logit model with lagged dependent variable

I have a panel dataset for stocks. My goal is to model and predict if the stock will close positive (1) tomorrow based on today's close (1/0) and other macroeconomic and firm-specific variables.So I ...
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580 views

Alternatives to Holt-Winters models when the seasonality pattern has changed

I am forecasting a series of daily volumes in terms of units processed for a particular time period (the period around Christmas). Historically, I have used a Holt-Winters model, with the minor ...
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813 views

Multiple short multivariate time series forecasting

I have a dataset for a lot of subjects (current testing dataset around 3000 subject, actual number is a lot bigger >40000). Each subject has 13 variables. The data was measured once per year for 11-...
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298 views

Building the covariance matrix for hts prediction intervals

In my previous question: Using information about covariance between ARIMA models in forecasting I was interested in the more general case of how to use the covariance matrix in prediction intervals ...
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44 views

Neural Networks for predicting Energy at particular date

I am trying to predict Solar Energy value at particular date.So,for this I am applying Artificial Neural Networks model.I am having problem in deciding activation function. Since sigmoid function ...
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253 views

Best measure for multiple time series modelling prediction methods?

Newbie question, sorry. I have a highly seasonal monthly time series, predictable with no exogenous/independent variables and no obvious trend. I want to show that a suitable state space model (using <...
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59 views

Forecasting method used for predicting the date of some events

If i'm working in a car company and I have some data for every customer i.e. Their license plate Date of their car's service in the dealer Number of km in their car when they service it Their ...
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988 views

Repeated arima forecast returning warning and NA value

I have the code below which trains a model with some predictors, forecasts it one step, appends the forecasted value on the original training data and then tries to feed that back in and train and ...
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553 views

Difference between estimation and prediction in simple linear regression model?

Here is what my notes say about estimation and prediction: Estimating the conditional mean We need to estimate the conditional mean $\beta_0+\beta_1x_0$ at a value $x_0$, so we use $\hat{Y_0}=\hat{...
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272 views

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 ...
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1answer
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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277 views

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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574 views

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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1answer
53 views

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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1answer
78 views

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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47 views

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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1answer
62 views

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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149 views

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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297 views

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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138 views

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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62 views

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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3answers
637 views

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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65 views

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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141 views

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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228 views

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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76 views

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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1answer
50 views

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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310 views

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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492 views

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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938 views

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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168 views

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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300 views

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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1answer
83 views

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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1k views

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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63 views

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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75 views

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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256 views

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 ...
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1answer
135 views

Sequential semi-automatic model selection of time series forecasting

I have a number of univariate time series that I would like to incorporate in a production system. I have daily data from a month and I would like to forecast every day the corresponding values for ...
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46 views

Forecasting an individual based on a representative group

I’m trying to forecast demand for an individual based on historical data of many individuals, but I’m having trouble finding examples of this. For example: I want to forecast the demand for a single ...

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