Questions tagged [forecast]
The forecast tag has no usage guidance.
103
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Doubt with Forecast values with orange
I would be very grateful if anyone can help me with the following situation.
I have a table that receives seven data records with values from 1 to 43 at random, for example:
With SQL I can determine ...
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Statsmodel VAR - add future external data - forecastr
Currently I am forecasting future values using following code:
...
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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] ...
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Multivariate time series - predicting value on multiple correlated variables
I have a dataset of the following structure:
daily sales data for the last 5 years
monthly economic trends (there is actually more)
The objective is to forecast sales on daily & monthly level ...
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What are some good methods for evaluating the disaggregation ratios in a top down approach?
Say we are forecasting at a high level (Department - Week) and we want to break it down to (Category - Week) level.
I want to find out which department's disaggregation ratios needs to be improved.
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Consumption rate on a small dataset with variability
I am looking to find the consumption rate, or how fast I am consuming energy so that I can later predict when my energy will reach a certain threshold. My dataset is fairly small and looking to see ...
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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,
...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 |...
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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 ...
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288
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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 ...
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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 ...
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(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: ...
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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
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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 ...
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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 ...
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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 ...
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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) ...
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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 ...
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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:
...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 ...
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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 "...
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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 ...
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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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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:
...
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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....
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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 ...
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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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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 ...
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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 $\bf{y_o}$) ...
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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
...
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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 ...
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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 ...
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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
...
