Questions tagged [forecast]

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How to do Time Series Forecast for data appearing on the same day for different Fiscal Years

I've been trying to figure out a solution to this problem for the past couple of weeks and after all my efforts I realized this is a very niche problem. I'm trying to forecast data for event ...
Minhaz Khan's user avatar
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1 answer
47 views

Timeseries Sales Forecasting

In my current work sales forecasting and budgeting is being done rather classical way: Take the sales from last year for comparable date and add or decrease X% on top to reflect recent trend. This ...
miroslaavi's user avatar
1 vote
1 answer
60 views

Best ML models for long term time series forecast

I have a project to make a long term prediction (like 5 years) of electricity production by types of power plants (solor, wind, coal, nuclear etc.). I have access to time series data in MW [megawatts] ...
Dan Jírovec's user avatar
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1 answer
594 views

How does one perform a Canova-Hansen test in Python?

I am referring to the documentation here, but it does not give many examples on how to actually perform the test. I have a pandas dataframe with two columns: Column 1 is first day of every week, ...
Vik's user avatar
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Demand Forecasting/Regression task for new products

I'm currently at the end of my master's degree and have to solve a data science problem. I am currently kind of stuck and need some kind of advice to get better results. I want to share the task I ...
Opa Knackfaust's user avatar
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1 answer
80 views

Why there is a gap when generating lags in time series?

I just started heading into time series forecasting, and a friend of mine who is doing this for several years showed me one of his projects. In his project, he was forecasting monthly sales quantity ...
user137566's user avatar
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1 answer
304 views

Which dataset for multivariate time series forecasting

I'm trying to forecast Real estate Price , it's not a prédiction. But a forecast Like the Price of a an appartement in 2023 or 2024, i'm asking about how should be my dataset ? Can I use a dataset ...
Djakarta_zero's user avatar
1 vote
0 answers
25 views

Forecasting out of sample with Fourier terms as regressors

I'm trying to create a multivariate multi-step-ahead forecast using machine learning (weekly and yearly seasonality). I use some exogenous variables, including Fourier terms. I'm happy with the ...
gogo88's user avatar
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1 answer
34 views

Forecasting profit based on allocation of labor and time-series data [closed]

Situation: a store sells services A & B, and we have historical data for daily sales/revenue/profit of each service. The store is interested in whether they should staff for more of service A or ...
user130771's user avatar
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0 answers
16 views

Forecast methodology for geographic variables that are somewhat related

I'm creating time series forecasts for different geographies and wanted an expert opinion on how I can take into account geographic relationship to improve my model. Is there an algorithm that's ...
Aks's user avatar
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1 answer
37 views

Best forecast model for insurance policies volumes

I am new in forecasting and I am studying a dataset from an insurance company that contains the volume on a monthly basis of new policies, renewals & cancellations. New policies of a given month ...
Minos's user avatar
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1 vote
0 answers
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Demand forecasting with marketing budget data

I'm trying to build a demand forecasting model to predict future daily orders of an online food takeout service (similar to UberEats or DoorDash). My first model uses a univariate approach, which is ...
drawar's user avatar
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0 answers
27 views

Impact of covid19 in forecasting models

I have sales training data from 2019-06 to 2020-06 and I have to predict sales from 2020-06 ...
David Masip's user avatar
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1 vote
0 answers
54 views

How to model a conditional demand forecast model as ex-ante forecast for a moving population?

Goal: I am trying to forecast demand from a specific population given a specific promotion on a certain period of time frame. The data is of the format: date | promotion % | sales in 1000s(y) 01-Jan |...
Ronak Agrawal's user avatar
0 votes
2 answers
4k views

Time series forecast for small data set

I am new in data science so please accept my apology in advance if my question sounds stupid. I want to do a time series forecast of outage mins in the current regulatory year. The regulatory year ...
user2293224's user avatar
1 vote
2 answers
369 views

Low precision on classification model

I am working since some months on a prediction from lead to a sale. Someone makes a lead on my website and I want to predict if this user will make a sale. I have these metrics on the test data. Now ...
Mutatos's user avatar
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41 views

How to condition your neural network to seek a specific amount of output? [closed]

I transformed a time series with collection values ​​from 0 to 100 into a windows of 60 elements with ...
Luis Henrique's user avatar
2 votes
1 answer
32 views

(Not a programming question) Is there a common word to indicate predict or forecast

The general understanding is: Predict: past value - could be data the model has seen (data from train set) or past data model has not seen (data from test set) (together in-sample data) Forecast: ...
gammay's user avatar
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Time Series Analysis / Modeling with auto_arima

I recently dived into Time Series and was attempting at doing some data analysis and modeling. I'm using the following dataframe ...
James Arten's user avatar
1 vote
0 answers
14 views

Ljung-box test on weekly percentage of total quarter bookings

I have a data on the weekly percentage of the total quarter bookings. The data looks as follows (note: weekly percentages add up to 100 for each quarter) : (not real data) I used the Ljung-box test ...
Saqib Ali's user avatar
  • 111
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0 answers
25 views

Multiple Values for One Day

I have two questions. 1- I have weather data of 10 turbines and I know their collective production(Power).I also know maximum power a turbine can make. How can I forecast collective production if I ...
MK_07's user avatar
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2 answers
84 views

Convey time lag information to a linear regression model

I am using a simple linear regression to predict the number of units an item has moved and price of the item is one of the input parameters. For a few items, the older prices are not relevant and ...
AntonySamuelB's user avatar
1 vote
1 answer
107 views

How to measure/rate the effect of a exogenous covariate in a ARIMAX Model?

I have an ARIMA model, I'm trying to figure out how much an external variable (exogenous covariate) could improve the forecast, so I need to "synthesize" a rate that tell me the usefulness (or impact) ...
Raffaele Giannella's user avatar
0 votes
1 answer
310 views

Sliding window approach using SVR & LightGBM

I'm working on a multivariate time series forecast using a couple of ML algorithms (Neural Networks, Support Vector Machines & Gradient boosting algorithms). I need to measure the performance of ...
zrilman's user avatar
3 votes
1 answer
2k views

ValueError from statsmodels ExponentialSmoothing

I've been having a frustrating issue with the ExponentialSmoothing module from statsmodels. My data is a pandas series with 74 weekly data points that looks like this: ...
gucciontoast's user avatar
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0 answers
4k views

How to fix "'The `start` argument could not be matched to a location related to the index of the data." Error?

When I try to predict the results using ARIMA for a specific train/test split, its throwing an error like this: "'The start argument could not be matched to a ...
Uday T's user avatar
  • 342
1 vote
1 answer
11k views

Auto.arima with xreg in R, restriction on forecast periods

I am using the forecast package and implement auto.arima with xreg. Here I want to forecast ...
Zuber's user avatar
  • 13
1 vote
0 answers
58 views

How to interpret the graph representing the fit provided by the ARIMA model?

I'm following this tutorial here to build an ARIMA model in R. I've done a Forecast using a fitted model in R. I specified the forecast horizon h periods ahead for predictions to be made and used ...
ilni's user avatar
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0 answers
20 views

How to explain calm period in energy consumption

I have a dataset of energy consumption that looks like this: I got it from Kaggle.com and all it says is that it's energy consumption data from PJM (this is the PJMW_hourly that corresponds to the ...
John Cataldo's user avatar
3 votes
1 answer
89 views

Next year forecasting with monthly data from many, correlated, non-monotonic trends

I have trend data from many health departments in a local territory (eg. cardiology, orthopedics, etc...). These trends represent health service (visits, diagnostic, admissions) production, service ...
Bakaburg's user avatar
  • 185
3 votes
2 answers
126 views

How can I go about building a model for large number of outputs?

I have previously worked on small-scale feedforward neural network problems. But I have started working on a new project where the goal is to predict air quality in 25 locations throughout the ...
maximusdooku's user avatar
1 vote
0 answers
84 views

Model for time series analysis

I'm new to data analysis and ML in general. I'm working with some friends on this problem: We're trying to predict when a component of a machine will stop working properly so the client can change it ...
Z3r0's user avatar
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1 vote
0 answers
317 views

Predicting Wave Trends of Candelestick Charts in Tensorflow (JS)

I'm relatively new to ML but my goal it to use Tensorflow.js and build a ML model that can help me detect a certain wave formation for an automated trading system. Examples of the 3-leg pattern I am ...
parliament's user avatar
5 votes
5 answers
50k views

Additive vs Multiplicative model in Time Series Data

The above time series plot is a daily closing stock index of a company. I want to know which model between additive and multiplicative best suits the above data. I know what the two models are, but i ...
Jor_El's user avatar
  • 231
2 votes
2 answers
876 views

Analysis of Time Series data

The below graph is a scatterplot of daily stock price. My aim is to predict future stock price of the company. From the scatterplot it seems that it is a multiplicative model, so I tried to "...
Jor_El's user avatar
  • 231
1 vote
0 answers
43 views

forecast product demand in one week using machine learning approach

I'm trying to predict product demand in store. The predictors I have include price, competitor's price, store ID, date. My target variable is sales volume (in a particular store). What I need to ...
zesla's user avatar
  • 181
2 votes
1 answer
106 views

how to predict content based demand

this is my first post at ds StackExchange, so please be gentle and let me know if something is not clear :) I have many products (>1M), and I save all the products purchases in a DB with a time stamp....
data_3's user avatar
  • 21
0 votes
1 answer
33 views

ML technique to predict next year output based on text quantities [closed]

I have a random data that I would like to predict how much a quantity will be in 2020. The data looks like this: ...
user102859's user avatar
1 vote
0 answers
73 views

Tuning a sequence to sequence model

I have written a variable length sequence to seqeunce autoencoder in keras using this tutorial as a guideline: https://blog.keras.io/a-ten-minute-introduction-to-sequence-to-sequence-learning-in-keras....
Aesir's user avatar
  • 458
5 votes
1 answer
415 views

Is an Arma model equivalent to a 1-layer Recurrent Neural Network without activation function?

Given a time series $f(t)$ to forecast, let us consider an Arma model of the form: $$ f(t) = c + \sum_{i=1}^p a_i f(t-i) + e(t) + \sum_{j=1}^q b_j e(t-j) $$ where $e(t)$ are the forecast errors. On ...
user2682877's user avatar
4 votes
1 answer
6k views

Monthly trend with fb prophet-Interpreting the graph

I have monthly data with month/year in one column and price on another. I would like to get a yearly trend with fb prophet library in python (how to use monthly data with the library is explained at ...
Munira's user avatar
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1 vote
0 answers
54 views

Specific data formatting techniques for discontiguous time series?

I'm facing a predicting problem for food alerts. The goal is to predict the variables of the most probable alert in the next x days (also any information I could get about future alerts is really ...
Rodrigo Díaz's user avatar
1 vote
0 answers
33 views

Observation Operator - Data Assimilation

In data assimilation, one assumes the existence of a observation operator $\mathcal{H}$ that maps the model-state vector $\bf{x_b}$ to $ \bf{y_b}$ (the model-equivalent of the observations $\bf{y_o}$) ...
Akshay Bansal's user avatar
1 vote
1 answer
41 views

Strategies for continuously assessing and improving model performance

I am building a supervised machine learning model to generate forecast. So I would have historic data like this: SKU, Month, .... other features, Actual Volume ...
The Lyrist's user avatar
1 vote
1 answer
4k views

How to calculate prediction error in a LSTM keras

I have an LSTM which I have constructed and run in keras using python. I use this model to predict $n$ points into the future for a time series forecasting problem. When I use a method such as ...
Aesir's user avatar
  • 458
1 vote
2 answers
198 views

What are some appropriate models to use for inventory forecast based on consumption history or trends?

I am working on an inventory management system where I have daily/monthly/yearly consumption history for a particular item, which may or may not follow a repeating trend. In order to forecast demands ...
Zobayer Hasan's user avatar
0 votes
1 answer
37 views

which forecasting models could be chosen?

I'm new for data analysis. I got some data from the regional environmental center. Measurements: Datetime, PointID, SubstanceID, Value (substances concentrations in air), MeteoID ,NextValue ...
zeroFour28's user avatar
1 vote
1 answer
196 views

Fully endogenous models for predicting multivariate time series

I have a formal social science background but I am new to data science. My interest is in building predictive models for applications in the social sciences, mostly (but not only) in economics. I am ...
Beginner's user avatar
1 vote
1 answer
752 views

demand forecast for B2B

I am attempting to create a demand forecasting model in python to predict future sales of a particular category of product, using historical sales data. We are a B2B company, which means that we ...
pynewbee's user avatar
  • 131
1 vote
0 answers
184 views

Naive/ Persistent Models & 7 Day Forecasts

When determining the baseline performance using a persistent or naive model I understand it to be using the value of the previous time step as the prediction for the next time step and then ...
Wayde Herman's user avatar