SAS
Building a Large-Scale, Automated Forecasting System
SAS

Building a Large-Scale, Automated Forecasting System

This course is part of Analyzing Time Series and Sequential Data Specialization

Taught in English

Jay Laramore
Marc Huber

Instructors: Jay Laramore

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Course

Gain insight into a topic and learn the fundamentals

Intermediate level
Some related experience required
10 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

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Assessments

19 quizzes

Course

Gain insight into a topic and learn the fundamentals

Intermediate level
Some related experience required
10 hours (approximately)
Flexible schedule
Learn at your own pace

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Build your subject-matter expertise

This course is part of the Analyzing Time Series and Sequential Data Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 10 modules in this course

In this module you get an overview of the courses in this specialization and what you can expect. Note: This same module appears in each course in this specialization.

What's included

1 video1 reading

What's included

1 video2 readings1 app item

In this modules you'll get an overview of the functionality used in the course. We'll describe how objects and methods in the Automatic Time Series Modeling, or ATSM, package in SAS Visual Forecasting can be combined to solve the large-scale forecasting problem. We'll also describe how the configuration of objects and information flows change depending on what stage of the automatic forecasting process you are in.

What's included

6 videos1 quiz

In this module we'll use the TSMODEL procedure to perform time series accumulation and missing value interpretation. We'll use packages for PROC TSMODEL, which are blocks of code that can be inserted within the flow of your PROC TSMODEL code to perform specialized tasks for both data preparation and analysis. Then, we'll discuss time series hierarchies and how to use a BY statement in PROC TSMODEL to create a hierarchy.

What's included

13 videos5 quizzes1 app item

In this module, we'll use the ATSM package in PROC TSMODEL to perform automatic forecasting, model selection, and specification. We'll walk through the process for declaring and using the many different ATSM objects and discuss how and where each object fits within the automatic forecasting process.

What's included

8 videos2 quizzes1 app item

This module describes and illustrates functionality for creating your own custom models in the forecasting system. We'll provide step-by-step instructions for building a custom specification and then modifying the automatic model selection process to include your model as a candidate for all series in a given level of the data hierarchy.

What's included

7 videos2 quizzes1 app item

In this module, we'll generate event variables three different ways. First, we'll use the ATSM package to create and implement predefined event variables. Second, we'll create event variables using the HPFEVENTS procedure. Third, we'll perform conditional BY-group processing for event variable creation. Next, we'll use and identify ARIMAX and ESM models, produce model selection lists, and select a champion model. Using the selected champion model and passing the predefined event variables to the TSMODEL procedure, we'll generate automatic forecasts and output model estimates and fit statistics.

What's included

12 videos4 quizzes1 app item

Reconciling statistical forecasts occurs after the automatic model generation, selection, and forecasting processes are done. In this module, we describe the reconciliation process and illustrate system tools and options for reconciling statistical forecasts we generated earlier in the course.

What's included

7 videos2 quizzes1 app item

This module covers a variety of topics. First, we'll discuss system tools and best practices that have the potential to improve the precision of your system forecasts. These include best practices like honest assessment for champion model selection and system tools like outlier detection and combined model forecasts. Next, we'll describe options and best practices associated with rolling the system forward in time.

What's included

14 videos2 quizzes1 app item

In this module you test your understanding of the course material.

What's included

1 quiz

Instructors

Jay Laramore
SAS
1 Course477 learners
Marc Huber
SAS
2 Courses7,368 learners

Offered by

SAS

Recommended if you're interested in Data Analysis

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