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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44 views

Smoothing train/test data

I am currently working on time series forecasting. I know that the first step is to divide the time series into train and test. Then I also understand that I have to normalize the test set using the ...
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Forecasting surface visibility with (right-)censored data

I have a bunch of surface visibility data measured at several ground weather stations over a certain period of time. The data for some of the stations are right-censored, e.g. a significant percentage ...
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Time series forecast with multiple time series

Supposing that I have 1000 data of characteristics of a machine (Period = 1..1000), with 6 dependent variables (Pressure, Speed, Temperature, Sound, Noise, and Vibration). Most of these variables ...
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32 views

How to graph ARIMA forecasts vs past values in R

I have performed an ARIMA model and I am happy with my results. Now I am trying to show that my forecast is good. Is it possible to create a graph that shows the forecast vs past values? What I am ...
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40 views

Forecasting two part ARIMA-GARCH model

I am conducting the ARIMA-GARCH model in two stages. First, I assess the ARIMA model and then apply GARCH model on the residuals from the ARIMA model. My model looks like this: ...
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49 views

Time series forecast where each measurment is already averaged and has a spread

I would like to forecast a time series consisting of time averaged (everything happening during 15min intervals is averaged and recorded with a timestamp of the start of messurment) quantities (...
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21 views

Cox PH Tenure Handling

I'm working on creating a survival model to forecast customer retention using the Cox Proportional Hazard model in R. I'm using the tenure of existing customers, in addition to other metrics, such as ...
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1answer
55 views

Forecasting aircraft flights per month

I'm trying to solve a time series forecasting problem, specifically I want to use historical data with an aspect of COVID-19 impact on global and regional aviation, number of new COVID-19 cases per ...
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87 views

Prediction intervals from Linear regression and Arima for DYNAMIC forecasting

I am comparing prediction intervals from linear regression and ARIMA for a simple AR(1) model: p = lag(p) The models were built on monthly data from 2003-2013 years. Predictions were made for 2014 ...
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ARIMA models: maximum reasonable horizon year, validation, model sensibility if extra year is added to sample

I am modelling a yearly univariate time series with 50 observations (1970 – 2019). I am interested in fitting an ARIMA model for forecasting purposes (in R). I have the following questions: What is ...
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386 views

Time Series Forecasting: ARIMA\VARIMA vs Machine Learning \ Deep Learning

I am working on the development of a time series forecasting, and I have some doubts on the model I should use to achieve better results. PREMISE: Multivariate Time Series: my time series is a ...
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87 views

Forecasting: best practice for including time-series data with different availabilities (missing data)

I have hourly time-series data with n inputs and a target variable. The target should be predicted at 07:00 a.m. for the next 48 hours. Some inputs are only available until 23:00 of the previous day. ...
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macroeconomic regressors as xreg in ARIMA - differencing required?

I'm forecasting a timeseries that has both trend and seasonality component, which is why I am using ARIMA. Without providing external regressors, the best model selected (in training) has the ...
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Is there anyway I can limit my forecast to a upper limit using bsts package?

I am using bsts package for forecasting. I need my forecast to be less than the upper limit. Like shown in the below figure. FaceBook Prophet allows this by an option. I would like to do the similar ...
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1answer
47 views

Out of sample MASE

When calculating the MASE, the original paper suggests using the in-sample naive forecast error for scaling of the out of sample forecast error. When i use the the MAE generated by a naive forecast on ...
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Calculate prediction interval with stats::predict

I'm forecasting for the first time, so please for some patience. I want to calculate lower bound of 95% interval on my point forecast. I have the following model for estimation and forecasting a ...
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152 views

Box Cox Transformation in auto.arima

I'm working with ARIMA models and was wondering about the necessity of BoxCox Transformation. When applying BoxCox on my training-set BoxCox.lambda(train) it ...
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28 views

simple linear regression forecast in matlab

How could I do a linear regression forecasting in Matlab, please? I am not asking for the code itself, but for some guidelines on how can I structure the problem and what to use. I have three ...
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What are the recommend approaches for adjusting forecasts made at a detailed level, to match a forecast made at an aggregate (total) level?

Intuitively, I have a greater confidence in a forecast performed on data at an aggregate (e.g. total company) level than the sum of forecasts at made a detailed level (e.g. product). However, when ...
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2answers
59 views

Why is there variation in the trend-cycle component despite using additive decomposition?

So, I've been reading Rob Hyndman's Forecasting book, and I'm now at the part of time series decomposition. Hyndman states that we use additive decomposition if the trend-cycle component or the ...
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47 views

Exponential Smoothing for many time series

I have a detailed dataset with a lot of time series. If I apply exponential smoothing (using for instance R) it will take me to much time to calculate an $\alpha$ (level parameter) and $\beta$ (trend ...
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26 views

Seasonal adjustment: Transfer of historical model to forecast values

I have a monthly time series provided by an external source, which contains both historical values and forecasts. I'd like to seasonally adjust the time series using X-13ARIMA-SEATS in R (package &...
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26 views

What I'm dealing with here VAR, VARX or something different?

I have to implement a time-series tool in my company, and I'm not sure what I'm dealing with, when looking at the old tool. We have one target variable (sales) and a lot of different independent ...
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53 views

Holt-Winters yields same coefficients no matter what seasonality parameter level set to

really appreciate any help, i've been running HoltWinters on data below, using R. Initially i just used ...
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1answer
53 views

Bayesian Forecast: Credible interval with predicted regressors

I want to do a forecast of let's say orders with a Bayesian linear regression, where orders do not only depend on time but also on another regressor, let's say accounts at time t. $$orders_{t} = \...
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Model generated 2 different results, which is the best SARIMA model?

I got 2 different forecasted results using different orders using SARIMA model. I am unable to choose the best model out of the two below. One have very low AIC but the SR1 co-efficient is close to 1 ...
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How to preprocess time series data with a high range for a neural network?

I have a multivariate time series where one feature ranges from 0 to 25 million while another simply goes from 0 to 800 thousand. Here is an example of my data: Giving these values to a neural ...
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Runtime Estimation for Multi-threaded processes with varying loads

This is much more of a computer-related question but I believe this requires statistical knowledge (which I'm not well versed and currently reading on the basics) so i hope you can bear with me. I ...
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Using forecast errors to cross-sectionally compare quality of two different data sources (using sLDA)

At a high level conceptually, I have two different data sources for panel data and I am trying to compare the quality of each data source by comparing forecast errors from models predicting an outcome ...
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49 views

Why does the STL function in R identify a seasonal component that increase with each cycle when robust parameter is set to TRUE?

I am working with weekly time series data in R. I want to check my data for seasonality and trend and I am using the stl() function in R. This is my data. ...
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63 views

get prediction intervals from Winters-Holt forecast method in python

I am trying to output predictions from a Winters-Holt forecasting model that I have made. I have found that libraries like Statsmodels have some tools to do that but impossible to find tutorials or ...
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102 views

Picking optimal lag values and intervals - multivariate time series

I'm working on my first project using time series: I have the weekly stocked amount of a product and I have to predict if it will go up or down (binary), looking for seasonality, I started trying this:...
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Multiple time series prediction problem

I would like to start a discussion. I am dealing with a consumption forecasting project and analyzing a database composed of more than 60k id counters. The goal is to create a system able to model the ...
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30 views

How to forecast $Y/std(Y)$ using a linear model?

How do I forecast $Y/std(Y)$ using a linear model? I'm currently forecasting only $Y$, and the model is producing results where the larger predictions corresponding to higher variance $Y$. For example,...
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45 views

Time Series & Stationarity

I know that Seasonality and Trend violate the principle of stationarity, so before modelling the time series with many statistical models like AR, MA and ARMA it's important to remove those components ...
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Should you preprocess data in SARIMAX or ARIMAX

Is it wise to scale exog variables in an ARIMAX/SARIMAX? We can assume that we have dummy variables and continuous variables (0-1000)
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1answer
44 views

Quality measure for predictive Highest Density Regions

An alternative to point, interval and density forecasts/predictions would be "predictive highest density regions (pHDRs)", i.e., HDRs for the conditional density of a yet-unknown future ...
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Why does my ARIMA model forecast drastic drop at the second timestamp in the prediction period?

I am trying to reproduce SPSS results with python. I'm using statsmodels SARIMAX package in python. My model produces forecasting results which shows sudden drop at '2020-08-01'. After '2020-08-01', ...
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9 views

Variance Ratio test for 3-D random walks

The variance ratio test proposed by Lo and MacKinlay (1988) is used to detect 1-D random-walk-like-behaviour. 1-D works great for time-series data, but I'd like to adapt this test for imaging data to ...
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30 views

Using hourly disaggregated data to predict aggregate daily counts through LSTM?

I have disaggregated person level data related to an infectious disease (COVID). I have about 4 months worth of data, which includes information like each person's sex, age, race, etc. What I ...
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Daily data - ARIMA forecast giving straight line

I'm trying to create a forecsast with ARIMA(3, 1, 1) and the forecast is giving me a straight line for out of sample predictions. Time Series Decomposition of original dataset: Original data set: <...
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1answer
81 views

Seasonal differencing and auto.arima

I've started studying different forecasting algorithms, using R. As an example, maybe not the best one (due to a lack of seasonality), I am using Facebook stocks. Training set: ...
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76 views

help with getting my data set up for cox ph (time dependent) to predict within time

I have many observations of data, and survival ranges from month1 to month24. i.e some patients will survive 1month, 2month, 3month, or go all the way to month24. For each observation, I'm trying to ...
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55 views

Multilevel Time-series Forecasting Model

I wanna do Demand Forecasting of product categories in different countries. The data structure of the data that I have is as follows: Date, Country, Product Category , Sales, and some additional ...
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2answers
92 views

Under predictions in Time series forecast

I have a time series which has increasing trend and is seasonal. I build a TSLM model, with trend() and ...
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39 views

What is the best practices on forecast by ssa?

I want to use the ML .NET SSA algorithm to forecast someone weight by age with upper and lower bounds. I can use someone data to train a model, but the growth paterns are little diferent per person. ...
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3 views

Should transformed models be back-transfored before penalization? And should ensemble forecasts from these also be penalized? From the same data?

I have generated a number of regression models in an effort to predict a particular outcome. All the models are based on the same data over the same period. They include, e.g., a vector error ...
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93 views

Is it possible to predict survival probability of the future (unseen) time points (in R)?

I have a time dependent cox model from 2018 to 2020. Running the cox model, I can look at survival probabilities from time0(month 0) to time24(month24) for each individual observation. Great! Now, I ...
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38 views

Consistent offset/lag in time-series prediction using Neural Network (all code provided)

I'm using a neural network (keras package) to predict Bitcoin prices 48 hours in advance. The issue is that for some reason, my predictions are "correct" but they are lagging behind the true ...
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Forecasting (financial timeseries) - differenced levels vs returns

While I am new to forecasting, I have spent a significant amount of time looking into the stationarity requirement of forecasting models such as linear regression, linear regression with ARIMA errors, ...

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