All Questions

Tagged with
Filter by
Sorted by
Tagged with
0
votes
1answer
37 views

Modeling non-linear (short) time series and cross-validate them

beginner data scientist here. Time series analysis is a completly new area for me, so please correct me if i write something that makes no sense. I have many multivariante short time series, between ...
0
votes
0answers
17 views

Pricing transfer prices for oil hub? 390 Days of prices given

Need some input in how to attack this problem. Given are 8 timeseries: UK Oil price, Delivery Quarter 1 2020 UK Oil price, Delivery Quarter 2 2020 UK Oil price, Delivery Quarter 3 2020 UK Oil price, ...
0
votes
0answers
14 views

Time-series forecasting of weakly correlated, univariate series

Given an event that happens with a probability of $\lambda_1$, and another event happens with a probability of $\lambda_2$, what is the probability that they both occur? I have a dataset of ...
0
votes
0answers
16 views

Pattern between different services

To start with, I have very limited knowledge regarding models / stats. We have few services which are interdependent. Let's say we have 5 services, A, B, C , D and E. We can roughly have a mapping ...
2
votes
0answers
103 views

Obtaining from scratch the volatility in GARCH model using R?

I'm trying to obtain the same vector of volatility by myself $\sqrt{h_{t|t-1}}$ of a Garch Model, that I obtained "automatically" using the function "ugarchfit" from the package "rugarch". So after ...
3
votes
0answers
62 views

Time series model for demand forecasting?

I have a time series $Y_t$ (example:university applications received in a certain month) which I want to forecast. I have another time series $X_t$ and I know that $Y_t$ is related to past lags of $...
2
votes
0answers
36 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 ...
2
votes
4answers
134 views

Is it acceptable to scale a model based on “intuition”?

Suppose that a model has been produced that will predict the total number of customers in a business. You are generally happy with the distribution of the model and believe the trends shown by the ...
0
votes
4answers
382 views

How to determine the best forecasting model for this type of data?

I am working on teaching myself some forecasting techniques that I can use in the future. Imagine a shopping mall. The mall contains many shops which each sell different products. I have a bunch of ...
3
votes
1answer
184 views

What is parameter instability? How can I measure it? [closed]

What is parameter instability and how can I measure it? If my model is having a hard time to forecast out-of-time samples, could parameter instability or populational instability be the cause of it?
0
votes
1answer
226 views

Regression Time based model [closed]

Say that I am trying to predict sales for the next year and I have a dataset that looks like this. ...
1
vote
0answers
43 views

ARMA model in R that accounts for models/data of previous years

I am attempting to forecast student enrollment for fall semesters. Enrollment begins about 90 days before the semester starts and closes 20 days after. I have used ARIMA and the forecast package in ...
1
vote
1answer
87 views

Predicting online revenue next month: Time Series or Regression?

Seeking guidance on approach. I have some marketing spend data along with historic target variable revenue. If management would like to estimate online revenue over the next 3 months given a media ...
0
votes
0answers
36 views

Approaches to forecasting hundreds of time series at once

I have several hundred time series that I need to forecast for. Some of these time series have a machine id number in common and provide somewhat similar behavior. Some of the time series are also for ...
1
vote
2answers
881 views

Interpretaing Arima Model Output with Exogenous Variables

I am using R "Forecast' package for prediction of churn by including external variables. However, in my case its bit confusing. What I expect when you introduce more titles a less people will live. ...
1
vote
1answer
67 views

How to model a series with a shock in all independent variables

My problem is a small sample of quarterly macro data with only about 55 observations. During the observed period there were several shocks, one of which happened four years ago and was rather huge, ...
2
votes
1answer
136 views

VAR model fitted: Causality or coincidence?

I'm doing some studies on variables (included their lags) that could influence the response variable (y1). The model that best fits the data is a VAR model (Vector ...
1
vote
1answer
346 views

How does heteroscedasticity relate to predictive accuracy?

I understand that heteroscedasticity leads to problems with coefficient estimates of a model, but I'd like to know how it relates to predictive accuracy. After creating my original linear model, I am ...
0
votes
1answer
468 views

Choosing inner cross validation strategy for modeling time series data

We know that forward chaining a.k.a. time series cross validation is more appropriate than standard CV techniques in a time-series dataset. However, there's relatively little discussion around the ...
0
votes
1answer
38 views

Can someone help me conclude the advantage of decision trees over looking at the exact match probability in data?

Recently I'm helping a company building a model predicting if the web visitor is a potential high value customer based on visitor's web behaviors. To make the model easy to understand, I suggested to ...
201
votes
3answers
18k views

How to know that your machine learning problem is hopeless?

Imagine a standard machine-learning scenario: You are confronted with a large multivariate dataset and you have a pretty blurry understanding of it. What you need to do is to make predictions ...
11
votes
1answer
669 views

When have I to stop looking for a model?

I'm looking for a model between stockprices of energy and the weather. I have the price of the MWatt bought between the countries of Europe, and a lot of values on the weather (Grib files). Each hours ...
0
votes
1answer
777 views

Forecasting methodology and k-fold cross validation for a vector autoregression

This is a follow up question the question that can be found here, and is a result of me having implemented (after as careful evaluation as I'm capable of) the alterations and changes suggested. Below ...
18
votes
2answers
26k views

VAR forecasting methodology

I am building a VAR model to forecast the price of an asset and would like to know whether my method is statistically sound, whether the tests I have included are relevant and if more are needed to ...
1
vote
1answer
65 views

Forecasting and making sense of data

This might seem very elementary or even silly, but all comments are much appreciated. As science major I do not have deep technical knowledge in statistics, so any guidance is much appreciated. Say ...
2
votes
1answer
100 views

Prediction or forecast error

I understand the general idea of different time series model fittings, calculations, and model comparison. However, I am a little confused of understanding the forecast of a time series model. For ...
2
votes
1answer
68 views

Can it be as accurate to model child-variables to estimate a parent-variable instead of modeling the parent-variable directly?

With time series data, let's say you want to model the return of the S&P 500. Could you get as good or better results by modeling each stock, and aggregating them to estimate the return of the S&...
4
votes
1answer
749 views

Determining order of ARIMA model using Box-Jenkins. Correct approach / argumentation?

I obtained a couple of time series from estimating my (mortality-)model which I now aim to forecast with an appropriate ARIMA(p,d,q) model, which should be chosen with the use of the Box-Jenkins ...
1
vote
0answers
159 views

Need some help on discrete valued time series forecasting?

I have data on reservation requests for hotels (your booking information:searching date, check-in, check-out, # of rooms and etc. on hotel booking websites) and am trying to do some analysis on one ...
5
votes
3answers
669 views

How to take advantage of multiples series with the same behaviour for forecasting?

I'm quite new to statistics and forecasting, and I have to build a model to forecast monthly sales of different related products in a bunch of cities. Seasonal ARIMA seams to be a good model for that,...
1
vote
1answer
376 views

Principled way of combining time series with different spans and granularity into an econometric model

I want to forecast the price of something given various time series as inputs. The problem is that they are of different frequency (annual, quarterly, monthly, daily) and time periods (the more ...
0
votes
1answer
358 views

What statistical method to correct systematic error in the output of a economic optimization model?

I am working with an economic optimization model which attempts to model the dynamics of a certain commodity market (prices, quantities, production etc.) for different frequencies (monthly, quarterly, ...
2
votes
1answer
1k views

Is positive coefficient of price correct in a multiple regression model

I am currently undertaking forecasting of energy sales (kWh) for our industrial customers. From historical data gathered from 1993 to 2013, a graph of price per kwh against sales kwh shows a positive ...
2
votes
1answer
836 views

What econometric model to forecast a seasonal commodity demand while incorporating exogenous Information?

I have a monthly commodity demand and try to forecast this series for the next 5 years. Here is a plot: Of course, the natural approach to forecast this seasonality would be some kind exponential ...
6
votes
1answer
398 views

When forecasting sequential data is it best to use auto-regressive models or build a more traditional n x p dataset with features?

I'm familiar with the use of auto-regressive models when it comes to forecasting a single vector of time-series data. Is anybody familiar with a more traditional modeling approach, i.e. - creating ...
5
votes
0answers
8k views

Time series modeling with R on weekly data [closed]

I am trying to do time series modeling and forecasting using R based on weekly data like below - ...
0
votes
1answer
65 views

How to determine what method is being used?

I was wondering what time series model would forecast future values in such a static but decreasing manner? ( I'm talking about the values around where the circle appears, as apparently, the data set ...
2
votes
0answers
66 views

Forecasting & social influence data/experiment - Seeking research strategies

In my experiment, individuals assign probabilities to the likelihood of future events, and update their forecasts as frequently as they like. Most questions stay open (receiving new forecasts) for ...
9
votes
3answers
4k views

What model can be used when the constant variance assumption is violated?

Since we can not fit ARIMA model when the constant variance assumption is violated, what model can be used to fit univariate time series?
3
votes
2answers
839 views

Understanding forecasting in R

I am presently trying to learn R. I would like to be able to apply it more in my work environment as I am an analyst in the Health Care industry. I am presently trying to use R to forecast. What is ...
1
vote
1answer
1k views

Dividing and forecasting a normal distribution

I have a collection of real-world samples that I am trying to model and then forecast. There are 10 datasets – each has an increasing number of data points (from 1 to 10). The points are equi-...
4
votes
3answers
2k views

Forecasting time series based on a behavior of other one

Apologies for this vague and unclear question, I have no background in statistics. I have two vectors of time series data, covering a six month period. The data is in daily intervals (except for ...
3
votes
0answers
161 views

Modeling relative contribution of a variable

I am overthinking this for sure, but I am stumped. I have a historical data set of projects with hours of contribution by various positions. There are six types of projects. How can I model the ...