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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Do these forecasts imply the ARIMA model is misspecified?
I have a time series of a stock return over more than 2 years. It's stationary (Augmented Dickey-Fuller test is significant). The plot looks like this:
The ACF and PACF look like this:
I think these ...
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9 views
How to understand a time series reached its saturation point or maximum growth?
I am curious about how to find that a time series model reached its saturation point or maximum growth which doesn't change over time and stable for a while? Saturated can also be considered as not ...
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28 views
How can I remove trend of model's forecast when I use ARIMA model?
I have to forecast future energy consumption. I decided to use ARIMA model. But my model's forecast shows the wrong trend. The blue line shows true value. And the orange line shows my model's forecast....
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26 views
Good results with Linear Regression
I am experimenting with a data set that I have of revenue of few products. It is on a monthly level and I have 6 years of data with me.
As a preprocessing step, I've converted that data set into a ...
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12 views
M4 forecasting competition models in R [on hold]
Anyone knows if someone manages to compile the different methods submitted for M4 competition into a R package?
The methods were submitted separately and have been compiled here
https://github.com/...
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1answer
87 views
Why is time series forecasting different for each software?
I have 2 different software programs: SPSS, and Statgraphics. I am using them for time series forecasting but
Each one gives different arima parameters when using the auto ARIMA model, and
The ...
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1answer
28 views
Automated Fourier Term Selection in Batch Forecasting via Foreach
I'm trying to parallelize my batch forecasting via foreach, and I'm pretty comfortable doing this via auto.arima and ...
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15 views
Remove season and trend from multivariate tsibble [migrated]
I am using the stl() function to remove season and trend from a multivariate timeseries. I then want to keep to remainder term from the stl decomposition in order ...
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47 views
Can I use ARIMA with hour data for two year prediction? [closed]
I am trying to use ARIMA model for time series forecasting. My data consists of hour by hour energy consumption. I have data for one year. So I have total 24*365 observations for energy consumption. ...
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1answer
32 views
95% prediction interval for an ARMA(2,2) model
What would the formula for a 95% prediction interval for an ARMA(2,2) model be?
The specific model I am using is: an ARIMA(2,0,2) with non-zero mean, with the following parameter estimates:
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9 views
What is the way to find p, d, q value of non-seasonal, and P,D,Q value? [closed]
How to find the p, d, q value of non seasonal and P, D, Q value of seasonal part from a f and pacf plot in tone series Arima model.
Auto arima is not providing good results.
I want to use Arima model....
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27 views
Problem with forecasting in R [closed]
So basically i am working with the japan ir and ipi data from fred database. I did this work on eviews but i wanted to pass it to R. The thing is that in eviews you have the option to choose between ...
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Fitting and forecasting a multivariate time series model (VAR) in R
I have some quarterly time series data for accumulated total public expenses and the total budget that I want to forecast. I also have subsets of the total public expenses, eg. health expenses and ...
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27 views
Forecasting intermittent demand with Dynamic Negative binomial [on hold]
In this paper Forecasting the intermittent demand for slow-moving inventories: A modelling approach (International Journal of Forecasting). The authors propose an autoregressive negative binomial ...
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1answer
14 views
Machine leaning model to predict whether customer would go out of balance or not based on the historical trasaction data [closed]
I want to prepare ML model that would help me in predicting customer's zero balance event using models like time series forecasting or any other techniques. I am getting customers transnational data ...
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Regression for long tailed time series events
I have a set of values which are a time series and follow a long tailed skewed distribution.
I would like to understand what the best method might be to predict the next value in the series.
Do the ...
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1answer
80 views
How can I improve my ARIMA forecast in R?
I obtained the ARIMA forcast below from the following code:
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14 views
Suggestions for appropriate time series model , continuous outcome, time varying covariates
I am a dealing with a dataset which is as follows
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66 views
Can I use linear regression for predicting time series? [closed]
I have the percentage of defaulted clients in porfolio for different periods as target variable and macroeconomic factors as explanatory variables. Can I use simple linear regression? What other steps ...
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1answer
18 views
Acceptable Standard for MAPE
What is the general acceptable value of MAPE in industry ?. I am getting MAPE of around 24% on live data that has 48 data points in which 42 as train data and 6 as test data. I am trying to do ARIMA ...
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1answer
27 views
Forecasting method to use with large seasonal swing but otherwise stable data
I am attempting to forecast percentage of churn. However, I am running into issues. The churn is fairly stable except at each year anniversary point.
For example, data looks like this for the first ...
2
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1answer
18 views
Time Series Forecast with Only 2 Observations
I have a number that I need to forecast its distribution over a period of time (5-7 years). There are currently 2 past observations, but I'd need to forecast the distribution of the rest. What options ...
2
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1answer
36 views
How does the R function Arima () calculate drift?
The Arima() function in the R forecast package contains an "include.drift" parameter. Could someone explain how this is calculated and how it is included in point forecasts?
According to this post ...
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1answer
38 views
Does a Vector Autoregression Model truly avoids circular function issues?
Let's say you have a VAR model that estimates GDP and Unemployment among many other variables using a certain number of lags. This VAR model can estimate or regress GDP using Unemployment. And, it ...
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Is there a relation between the characteristic roots and the s.e of the arima coefficients?
in Forecasting: Principles and Practice there's a warning that
inverse characteristic roots close to the unit circle may be numerically unstable, and the corresponding model will not be good for ...
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21 views
How do I weight multiple forecasts based on Mean Absolute Percentage Error (MAPE)?
I have 3 forecasts that have different Mean Absolute Percentage Error values that were averaged for each forecast over a 6 month period at a monthly cadence against end of month actuals. How would I ...
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1answer
40 views
Time Series Analysis - ARIMA
I am trying to make sales prediction from time series data.
After performing a log transformation to the original data and differencing it by 1, I got a stationary dataset. So I plotted ACF and PACF ...
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1answer
32 views
Alternatives for Diebold-Mariano test when comparing the best forecast among many against a benchmark
Suppose I encounter a new forecasting method and I wish to evaluate it against a benchmark. I can obtain forecasts from the two methods and compare them to actual realizations and thus obtain the ...
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36 views
Deriving the general form of the best linear predictor $\tilde{X}_{n+m}$ of $X_{n+m}$ for AR(1) process in terms of $X_1, …, X_n$
I'm trying to derive the best linear predictor $\tilde{X}_{n+m}$ for $X_{n+m}$ for a causal, zero-mean AR(1) process $Z_t = X_t - \phi X_{t-1}$. My answer needs to be in terms of $X_1, X_2, ..., X_n$.
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8 views
Incorporate sales forecast uncertainty into product stock availability simulation
I work in a e-commerce and I’m estimating availability of our catalog products. The process (in its simplified form) looks the following. A customer order comes in and we fulfill it if we have stock ...
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2answers
19 views
Extract standard errors from Arima model applied to groups using sweep
I am following the sweep vignette on Forecasting Time Series Groups in the tidyverse, see here. sweep is the ...
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0answers
14 views
Covariance of prediction errors
I have an exercise to compute the covariance between the prediction errors, but I'm not sure if it is correct, this is the exercise;
I have an AR(1) model, $y_t = \phi y_{t-1} + \epsilon_t$, where $\...
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2answers
45 views
How to forecast number of event occurences in a certain time period?
I am attempting to predict how many times a certain event will happen in a time period. For instance, predict the number of time the event will occur in the next 5 hours. I have data going back a ...
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Are Random Forests limited for forecasting/projection purposes
Today a coworker came asking me if we could train a model that will predict some land prices and then use said model to predict on hypothetical data.
Let's say, I have a ...
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21 views
First difference or seasonal difference in VAR/VECM
I have monthly data on house price, rental price, wage index and interest rates. I want to use VAR to produce impulse response function.
Is there any reason why I should use first difference, x(t)/x(...
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1answer
27 views
Log-Log regression and cost function
I have made a very siple linear regression model having used log-log tranformation for the y and one of the independent variables: log(y)=B0+log(X1)B1+X2B2 where B0 is the intercept and B1,B2 the ...
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1answer
50 views
Are there any method to multivariate forecasting except for VAR?
I mean 2 or more dependent variables as multivariate.I know we can use VAR or VARMA to forecasting but are there another method except for ANN and VAR?
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1answer
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How to calculate seasonal naive quantile forecasts?
I was reading a chapter on prediction intervals and saw that the standard deviation is used to calculate "prediction" intervals. Earlier today I was reading some results from GEFCom2017 where ...
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3answers
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What's the difference between Time Series Regression and Forecasting?
I often see the concepts Time Series Regression and Time Series Forecasting refering to something similar but I don't see clearly what's the difference among these two concepts. By now, the idea I ...
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1answer
132 views
Inventory forecasting algorithm for wines?
I'm trying to figure out a good inventory forecasting algorithm for wine sales.
I have the following characteristics so far:
Wine sales are cyclical and not seasonal
Have incomplete time series: ...
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1answer
28 views
MAPE and SMAPE shift invariance (bias)
MAPE (Mean Absolute Percentage Error)
and SMAPE (Symmetric Mean Absolute Percentage Error)
both are sensitive when the TRUE ...
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0answers
12 views
How to figure out which features indicate similarity between time series?
I have a data set with the following data:
A large number of time series of sales for various products.
A large set (~100) of static features that describe each of these products (e.g. product ...
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2answers
66 views
Comparison of MAE and Mean to illustrate the error magnitude
I have predicted a time series with positive, zero and negative values. As error measurement I used the Mean Absolute Error (MAE).
In order to give the reader of my paper a better understanding ...
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40 views
Prediction of $X_{n+1}$ with Yule-Walker estimate
Consider a causal AR(1) process $X_t = \phi X_{t−1} + Z_t$ with $(Z_t)$ iid with mean 0 and finite variance. I am reading in a book, that $\phi X_n$ is the best predictor for $X_{n+1}$ because it ...
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1answer
30 views
Prewhitening with seasonal response and non-seasonal independent variable
I'm working to develop a forecasting model for a quarterly seasonal variable (quarterly estimated individual income tax payments) using several candidates for non-seasonal independent variables (...
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how to estimate hyper-parameters when cross-validating time series forecasting?
I want to evaluate several forecasting methods on the taylor time series using cross-validation.
How do I go about selecting the hyper-parameters for the methods? ...
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Is it necessarily incorrect to randomize train-test split for a time series random forest model?
As part of some preliminary research, I'm experimenting with a random forest classification model for predicting whether the S&P 500 will be higher or lower at tomorrow's close versus today's ...
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How does BATS model work?
I am using BATS on a univariate time series model. I have observed strange behaviour. I have data from 2016 to till date (weekly level). If actual are considered from 2016 to 2019 May, I have used ...
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9 views
RNN (LSTM) training on multiple time series
Regarding RNN training, We feed network a network -> point by point from the same time series (or image or smth else).
When we “switch from one time series to another”, what should be done or how ...
