A Practitioner's Guide and MATLAB Toolbox for Mixed Frequency State Space Models
Dublin Core
Title
A Practitioner's Guide and MATLAB Toolbox for Mixed Frequency State Space Models
Subject
mixed frequency, state space, Kalman filter, maximum likelihood, MATLAB.
Description
The use of mixed frequency data is now common in many applications, ranging from
the analysis of high frequency financial time series to large cross-sections of macroeconomic
time series. In this article, we show how state space methods can easily facilitate both
estimation and inference in these settings. After presenting a unified treatment of the state
space approach to mixed frequency data modeling, we provide a series of applications to
demonstrate how our MATLAB toolbox can make the estimation and post-processing of
these models straightforward.
the analysis of high frequency financial time series to large cross-sections of macroeconomic
time series. In this article, we show how state space methods can easily facilitate both
estimation and inference in these settings. After presenting a unified treatment of the state
space approach to mixed frequency data modeling, we provide a series of applications to
demonstrate how our MATLAB toolbox can make the estimation and post-processing of
these models straightforward.
Creator
Scott A. Brave
Source
https://www.jstatsoft.org/article/view/v104i10
Publisher
Morning Consult
Date
October 2022
Contributor
Fajar bagus W
Format
PDF
Language
English
Type
Text
Files
Collection
Citation
Scott A. Brave, “A Practitioner's Guide and MATLAB Toolbox for Mixed Frequency State Space Models,” Repository Horizon University Indonesia, accessed April 4, 2025, https://repository.horizon.ac.id/items/show/8280.