Questions tagged [forecast]

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2
votes
1answer
51 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 ...
4
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3answers
263 views

How can one generate future forecasts from probabilistic events?

I have an event "whether an item sold will be returned or not" which I can predict with a certain probability based on information gathered at the time that the purchase occurs (product features, ...
0
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1answer
158 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 ...
2
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1answer
114 views

Store's unseen items sales forecasting

I am working on sales forecasting problem.I am able to provide data about which items got sold and not sold to the algorithm.How to provide algorithm information about items that are not present in ...
4
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1answer
3k views

Kalman filter for time series prediction

I have the information about the behaviour of 400 users across period of 1 months (30 days). Across those 30 days I measure 4 different information (let's call it A,B,C and D), hence I have a total of ...
1
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1answer
20 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 ...
0
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2answers
867 views

Fitting an arimax model on out of sample dataset

I have built an arimax model where we have sales data across time as the response variable and price is one of the external variables. I used the below code to build a simple arimax model. I had data ...
5
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5answers
30k 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 ...
1
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1answer
157 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 ...
2
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3answers
2k views

Multi-Source Time Series Data Prediction

I was wondering if anyone has experience with time series prediction for data from multiple sources. So for instance, time series $a,b,..,z$ each have their own shape, some may be correlated with ...
1
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1answer
70 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) ...
4
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1answer
4k 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 ...
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0answers
13 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 ...
1
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1answer
22 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 ...
1
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0answers
26 views

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 ...
0
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0answers
15 views

Demand Forecasting - Error in predictions

I've been trying to do daily demand forecasting using the H2O AutoML package for using 4 years of daily sales data as the training set. However, the daily estimates always seems to find a range around ...
-1
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1answer
236 views

nnetar giving different output each time

I am using nnetar package for time series forecasting in R.But each time when I run the model, I am getting different output. i guess this is related to different random weight initialization at each ...
1
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0answers
22 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 ...
1
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0answers
33 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 |...
0
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2answers
184 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 ...
1
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2answers
77 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 ...
3
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1answer
697 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: ...
1
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0answers
33 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 ...
4
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0answers
98 views

Quantifying 'growth friction' when projecting target goals

As part of my DS work I spend some fraction of my time helping the team make growth projections, either for setting growth targets or when forecasting actual data. There is obviously a range of ways ...
4
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2answers
2k views

Analyze performance Poisson regression model on a time series(count forecasting)

I have tried to build a model to forecast the count of a particular variable.The model that was used for the purpose was poisson .Unfortunately ,i don't have enough stat knowledge to analyze the model ...
2
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1answer
26 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: ...
1
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0answers
33 views

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 ...
1
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0answers
10 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 ...
0
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0answers
22 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 ...
0
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1answer
590 views

Modelling promotions for demand forecasting

I am trying to develop a model to predict future demand for a product. Now, there are always some promotional events that affect the sales. I am trying to solve this problem using dummy variables. ...
5
votes
1answer
227 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 ...
1
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1answer
7k 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 ...
2
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2answers
631 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 "...
29
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1answer
10k views

Time Series prediction using LSTMs: Importance of making time series stationary

In this link on Stationarity and differencing, it has been mentioned that models like ARIMA require a stationarized time series for forecasting as it's statistical properties like mean, variance, ...
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2answers
32 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 ...
10
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2answers
4k views

Forecasting non-negative sparse time-series data

I have a time-series dataset (daily frequency) representing the sales of a product to a customer over time. The sales is represented as the following: $$[0, 0, 0, 0, 24, 0, 0, 0, 0, 0, 0, 0, 4, 0, 0, ...
0
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0answers
2k 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 ...
1
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0answers
45 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 ...
0
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0answers
16 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 ...
3
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1answer
69 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 ...
1
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0answers
74 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 ...
1
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2answers
119 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 ...
1
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0answers
190 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 ...
2
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1answer
95 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....
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0answers
38 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 ...
2
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3answers
2k views

How to use ML to forecast sales of a brand new product

I am working on a forecasting problem and came across this issue. How do I forecast sales of a brand new product? For example, a product has been introduced in the store and the store would like to ...
0
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1answer
27 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: ...
1
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0answers
60 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....
1
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0answers
38 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 ...
1
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0answers
21 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 $\bf{y_o}$) ...