Fitting State Space Models with<i>EViews</i>

Bossche, Filip A M Van den

doi:10.18637/jss.v041.i08

Cited by 8 publications

(3 citation statements)

References 6 publications

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“…Stata (Drukker and Gates 2011), Eviews (Bossche 2011), RATS (Doan 2011) and gretl (Lucchetti 2011). See also the special issue in volume 41, 2011 of the Journal of Statistical Software (Commandeur, Koopman, and Ooms 2011).…”

Section: Introductionmentioning

confidence: 99%

Automatic Identification and Forecasting of Structural Unobserved Components Models with UComp

Pedregal

2022

J. Stat. Soft.

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UComp is a powerful library for building unobserved components models, useful for forecasting and other important operations, such us de-trending, cycle analysis, seasonal adjustment, signal extraction, etc. One of the most outstanding features that makes UComp unique among its class of related software implementations is that models may be built automatically by identification algorithms (three versions are available). These algorithms select the best model among many possible combinations. Another relevant feature is that it is coded in C++, opening the door to link it to different popular and widely used environments, like R, MATLAB, Octave, Python, etc. The implemented models for the components are more general than the usual ones in the field of unobserved components modeling, including different types of trend, cycle, seasonal and irregular components, input variables and outlier detection. The automatic character of the algorithms required the development of many complementary algorithms to control performance and make it applicable to as many different time series as possible. The library is open source and available in different formats in public repositories. The performance of the library is illustrated working on real data in several varied examples.

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Section: Introductionmentioning

confidence: 99%

Automatic Identification and Forecasting of Structural Unobserved Components Models with UComp

Pedregal

2022

J. Stat. Soft.

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“…There are some commercial and open-source pieces of software similar and complementary to ECOTOOL: Econometrics and GARCH official MATLAB toolboxes [1], CAPTAIN [2], SCA [3], TRAMO/SEATS [4], forecast package in R [5], gretl [6], STAMP [7], Eviews [8], SAS [9], Stata [10], etc.…”

Section: Introductionmentioning

confidence: 99%

Time series analysis and forecasting with ECOTOOL

Pedregal

2019

PLoS ONE

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This paper presents ECOTOOL, a new free MATLAB toolbox that embodies several routines for identification, validation and forecasting of dynamic models. The toolbox includes a wide range of exploratory, descriptive and diagnostic statistical tools with visual support, designed in easy-to-use Graphical User Interfaces. It also incorporates complex automatic procedures for identification, exact maximum likelihood estimation and outlier detection for many types of models available in the literature (like multi-seasonal ARIMA models, transfer functions, Exponential Smoothing, Unobserved Components, VARX). ECOTOOL is the outcome of a long period of programming effort with the aim of producing a user friendly toolkit such that, just a few lines of code written in MATLAB are able to perform a comprehensive analysis of time series. The toolbox is supplied with an in-depth documentation system and online help and is available on the internet. The paper describes the main functionalities of the toolbox, and its power is shown working on several real examples.

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“…EViews 6.0 was released in February 2007, EViews 7.0 was released in January 2010, and an upgraded version, EViews 7.2, was released in mid 2011. Since our review of EViews 5.1 (McKenzie and Takaoka, ), the only thing close to a review of EViews that we could find was a narrowly focused discussion of the options for fitting state‐space models in EViews 6.0 by van den Bossche (). We therefore try to provide a broad introduction to EViews as well as indicating the key changes between the different versions of EViews.…”

Section: Introductionmentioning

confidence: 99%