State Space Modeling Essentials Using the SSM Procedure in SAS/ETS(R)

Course code: FSSM42

This course covers the fundamentals of building and applying state space models using the SSM procedure (SAS/ETS). Students are presented with an overview of the model and learn advantages of the State Space approach. The course also describes fundamental model details, presents some straightforward examples of specifying and fitting models using the SSM procedure, and considers estimation in SSM, focusing on the Kalman filter and related details. The course concludes with a variety of SSM modeling applications, focused mainly on time series.
1 200 EUR

1 452 EUR including VAT

Selection of dates
Do you have a question?
+420 731 175 867

and certified lecturers

recognized certifications

Wide range of technical
and soft skills courses

Great customer

Making courses
exactly to measure your needs

Course dates

Starting date: Upon request

Type: Upon request

Course duration: 14 hours

Language: en

Price without VAT: 1 200 EUR


Type Course
Language Price without VAT
Upon request Upon request 14 hours en 1 200 EUR Register
G Guaranteed course

Didn't find a suitable date?

Write to us about listing an alternative tailor-made date.


Target group

Time series modelers and analysts who want to take advantage of a flexible and visual approach to modeling sequential data

Course structure

State Space Models

  • introduction
  • reasons for using a state space model
  • state space model framework

Basic Modeling Using the SSM Procedure

  • identifying state space model components
  • fitting basic models

Introduction to the Kalman Filter and Estimation in the SSM Framework

  • state space models and regression
  • filtering
  • diffuse starting values
  • filtering results
  • smoothed estimates

More Modeling Examples Using the SSM Procedure

  • accommodating an endogenous input variable in an SSM
  • Demonstration: Specifying and estimating a transfer function model in the SSM procedure
  • a multivariate model
  • cointegration


Students should be comfortable with linear modeling ideas and have some experience with time series models such as Unobserved Components models or ARIMAX.

Do you need advice or a tailor-made course?


product support

ComGate payment gateway MasterCard Logo Visa logo