Prediction of the future events. It is a special case of [prediction], in the context of [time-series].
0
votes
0answers
13 views
Measuring the effect of an outside force on time series with trend and seasonality
Let's say I have a time series that shows daily traffic to my website. My website is getting more popular so there's a trend up, and the traffic is based on day of week so it's cyclical with a period ...
-1
votes
0answers
8 views
level shift outlier model
Does somebody happen to know how to calculate the forecast with the LS formula since it got denominator? I got confused because of that.
Here's the model I've been using for the forecast.
0
votes
1answer
13 views
When i run auto.arima I get different values for the parameter “d” and ndiffs using x regressors
Im new using r. Im performing a kpss test on my "y" variable and running ndiffs procedure, and in both cases get 1 for the parameter "d" , but when I run auto.arima with x regressors I get 0 for the ...
0
votes
0answers
14 views
Production Curves for Agriculture
The idea here is to fit a curve to production data in agriculture.
By a production curve I mean for example the output of a mine over time, peak oil production or the yield of a farm over time within ...
0
votes
1answer
26 views
Difference between forecasting model, forecasting method and forecasting function
I am new to the field of Business Analytics. Can anyone distinguish between forecasting model, forecasting method and forecasting function? According to the book forecasting function is is an equation ...
0
votes
0answers
6 views
Assess expected performance on trials with different parameters?
I work at an online retailer, and we sell our products by sending out push notifications to specific places about specific products. A particular notification is called an offer. I'm trying to assess ...
0
votes
0answers
6 views
Smoothing Predictions from HMM
I would say I do not have a strong foundation on stats, however, I am trying to use statistical tools for my research. I am using a hidden Markov model (HMM) to forecast day-ahead (hourly) solar ...
3
votes
0answers
22 views
Using multinomial logistic regression to make predictions [on hold]
I have run a multinomial logistic model in SAS with 5 independant variables and I need to use the results from this model to make forecasts of use of care. I have used the predicted probabilities from ...
4
votes
0answers
71 views
Is there a theoretical reason why simple models perform better than complex models on time series forecasting tasks?
Empirically, simple forecasting methods such as damped trend exponential smoothing, STL, or even random walks typically outperform more complex models such as higher order ARIMA models or ML based ...
0
votes
0answers
18 views
Differencing causes negative predictions
I have a non - stationary time series sequence which is based on counts. To convert the sequence into stationary I applied differencing, which converted the sequence into stationary but the sequence ...
0
votes
0answers
23 views
Panel Data and Prediction/Forecasting
I have balanced panel data for around 130 countries, over three years. I ran a fixed effects regression using 'country' as my panel variable, and adding dummies for 'year'.
I want to forecast the ...
1
vote
1answer
26 views
How to you measure the accuracy of a model that gives quantile forecasts or distributions of forecasts?
I've come across some recent demand forecasting approaches that present methods where instead of generating just a point forecast, the model outputs a set of forecast quantiles, or a distribution of ...
2
votes
1answer
147 views
Need advice on evaluating forecast accuracy in R
I'm trying to evaluate some software for forecast accuracy. It works by summing up all the orders from a number of locations for each month, then determines the best model out of a series of models ...
7
votes
3answers
807 views
Over fitting on purpose
Would it make sense to overfit a model on purpose?
Say I have a use case where I know the data will not vary much respect to the training data.
I'm thinking here about traffic prediction, where the ...
0
votes
0answers
26 views
Choosing a model
I am working on a sales forecast right now and I have created 4 models but I am unsure which one to use.
I have 17 Quarters of data(4 Full years + 1 QTR) and I am only looking to forecast 2 quarters ...
1
vote
2answers
28 views
Measuring error from regression results, is MSE appropriate here?
I used boosted regression trees on a dataset I was working on to predict how much a customer will spend in a given year. Here is a sample of the output:
...
0
votes
1answer
64 views
3
votes
2answers
43 views
Modeling Techniques for Sales Forecasting
I am working on a sales forecast right now and I am not sure what type of model to use.
I have 17 Quarters of data(4 Full years + 1 QTR) and I am only looking to forecast 2 quarters into the future ...
1
vote
0answers
21 views
Intuition about Exponential Smoothing parameters?
If I use Triple Exponential Smoothing with Additive Seasonality and let a statistical program optimize alpha, beta and gamma for me, is there something I can conclude about my data based on the ...
2
votes
0answers
27 views
Interpreting forecast predictions of log transformed data
Using the forecast function in R, I make a 1-step prediction for a log-transformed data set Y, ( Y = log(X) ). This prediction gives me a mean and a 95% prediction interval.
How valid is this ...
0
votes
0answers
50 views
Testing the validity of models for adjusting bookmaker odds into probabilities of real-world events
I'm looking at the use of bookmaker odds to predict the outcome of sporting events in which only two results are possible. A problem with using bookmaker odds to predict outcomes is that they include ...
0
votes
0answers
22 views
How to include outside temperature in visitor prediction model
I am developing a prediction model for visitors of a building. Outside temperature impacts the number of visitors - but i don't know how to include it as a regressors in the model.
This is an example ...
0
votes
1answer
13 views
Difference between regression tree and autoregressive tree model
I am using autoregressive tree model for forecasting but m confused between regression tree and autoregressive tree model. Are these same
0
votes
1answer
39 views
Time Series Cross Validation in R
I am trying to do time series cross validation in R using tsCV() function from the forecast package. I have a doubt regarding the forecast horizon parameter "h" in this function. If the value of h is >...
1
vote
0answers
23 views
Time series analysis where computing the exact value is possible (but expensive)
I have a stationary time series where it is actually possible for me to compute the exact next value. These computations are very expensive, and to speed things up I want to employ following scheme:
...
-1
votes
1answer
36 views
My neural network will run okay, but occasionally (every 1000) it provides an error. [closed]
I am using a neural network to forecast the direction of gold prices. I have created a neural network neuralnet within R. My programme runs well and i can get a prediction accuracy of about 51%. ...
1
vote
0answers
26 views
Multivariant time series forcasting
I have a multivariate time series data with Timestamps as( 'season' with four categories: 1,2,3,4, 'month' with 12 categories and 'day' with 5 categories excluding Saturday and Sunday) and I have to ...
0
votes
0answers
17 views
Switching attention - is there a statistical tool to mimic perceptive response?
I was driving this morning to work. Another car made sudden lane change. I noticed an interesting thing: for a brief moment my attention focused in this car. It almost physically felt that everything ...
0
votes
1answer
30 views
Ljung-Box test on a out of sample residue with good forecast
To test the fbprophet library, I created a very simple synthetic series and generated a model like this:
...
1
vote
0answers
24 views
Johansen test R - long term relationship covariance
I have two time series which are I(1) and co-integrated. I would like to make long term forecasts for one of the time series, given an assumed fixed value for the other. I used the Johansen test (ca....
1
vote
1answer
26 views
Macroeconomic effects. Effects of a time serie on another
I have a monthly time series for the provision in a financial institution. Take real data until december 2017 and predict it with a Bat model until June 2018 using R and I have an error of 0.12%. This ...
1
vote
1answer
42 views
Forecasting new period with Regression Model
Have a dataset which consists of item names (rows) and monthly values of sales (columns). My task is to predict value of sales for next month and I'm trying to use regression models for that. But the ...
0
votes
0answers
21 views
logistic regressions per item
I have sales performance data with boolean outcome of true or false that i want to analyse the main influence on outcome.
...
2
votes
0answers
24 views
How to refine a logistics population model? [closed]
I have to refine a logistic population model so that it more accurately fits a set of data and was wondering how to do this. The only way I can find is to use a variable carrying capacity however I ...
0
votes
0answers
79 views
AR(p) forecast is almost always above actuals in pseudo out-of-sample forecasting
I have a trouble with my out-of-sample forecasts. The task is to evaluate the out-of-sample performance in forecasting the CPI(price index). In order to do this, I have estimated simple AR(1) with ...
0
votes
2answers
49 views
Is there a way to add external regressors for exponential smoothing based models?
I'm trying to forecast a daily time series while taking into consideration the effect of weekends and holidays using different methods in R.
For arima() it was ...
0
votes
0answers
22 views
Sales Forecasting
I understand the sales of the product I am trying to predict is a function of the need for the product and its price. Should I model these separately and create a strategy matrix with segments like ...
0
votes
0answers
25 views
Why is WAPE always lower than MAPE [closed]
I'm running a time series forecast using ARIMA. I am using the following calculations for MAPE and WAPE. I expected to get a higher WAPE than MAPE because I'm not removing the zero actuals from my ...
0
votes
0answers
38 views
sarima model with additional regressors
I have fitted a SARIMA model for daily data with 5 regressor variables. In addition, I used Fourier terms to capture the seasonal patterns in the model according to the prof. Hyndman post on daily ...
1
vote
1answer
49 views
Can I apply ARIMA(p, d, q) model to testing dataset and make forecast with the testing dataset? Just like the scenario of regression model?
After I fit a sarima model with some historical sales data (for example A dataset), I get coefficients of sma1 and ar1. And I'd like to apply this model to current sales data (for example B dataset) ...
0
votes
2answers
42 views
Forecast sales and then ungroupto find individual sales
I hope you're doing well. I am trying to solve a problem for a brewery.
A brewery has 50 beer types in total out of which only 8 to 10 beers are available on tap for a single day i.e only 8 to 10 ...
1
vote
2answers
30 views
Forecasting sales: different methods
It's a bit untypical question I guess, but I hope you can help me. I know a little bit of statistics. I'm not a specialist, but I find it really interesting, so I learn in my free time. I need your ...
0
votes
1answer
58 views
What is a correct implementation of the moving average model
I would like to implement a moving average model in python as when I try to use the statsmodels library, specifically the ARMA(p,q) function and setting $p=0$ I get a lot of convergence errors in the ...
0
votes
0answers
36 views
How to test if time series data is random
I have many time series data sequences and I would like to produce forecasts for their behaviour in the future. In order to do this I am looking into several methods, but the underlying concept is ...
0
votes
0answers
32 views
How to interpret the Ljung-Box test output?
I am trying to forecast the univariate time series using two different neural networks. After training and testing, I have residuals (Actual - Prediction) with me for both networks say ...
1
vote
1answer
76 views
What more advanced methods can I use to predict future sales other than polynomial fitting?
I am using the polynomial fitting method to forecast the sales of a product throughout different years, where the polynomial is of degree 1.
The error is measured by the sum of the squared residuals.
...
0
votes
2answers
79 views
How to forecast daily time series with weekends and holidays?
I'm having troubles choosing which approach to adopt when trying to forecast daily time series while taking into consideration special days like weekends and national holidays. The two methods I'm ...
1
vote
1answer
47 views
What does that mean if neural network never overfits on a dataset?
I'm trying to predict a parameter with use of neural networks. The parameter is highly linearly correlated with some of its predictors (Pearson's r~0.9)(However, the influence of time may not be ...
0
votes
0answers
40 views
Are Bias-Variance trade-off and Mean Squared Prediction Error (MSPE) the same?
I was reading about the Bias-Variance trade-off in the textbook "Elements of statistical learning". Is the expected forecast error listed there the same as the MSPE?
0
votes
1answer
23 views
Can I roll-up forecasts to analyze against benchmark methods?
There's a software product (call it Main) we use to allocate parts to various locations. The way it works is it sums up the demand history of all locations to the part level. For example, if part A ...
