Graphical Tools for Exploring and Analyzing Data From ARIMA Time Series Models

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dc.contributor.author Meeker, William
dc.contributor.author Meeker, William
dc.contributor.department Statistics
dc.date 2018-02-16T03:47:28.000
dc.date.accessioned 2020-07-02T06:56:10Z
dc.date.available 2020-07-02T06:56:10Z
dc.date.issued 1999-03-29
dc.description.abstract <p>S-plus is a highly interactive programming environment for data analysis and graphics. The S-plus also contains a high-level language for specifying computations and writing functions. This document describes S-plus functions that integrate and extend existing S-plus functions for graphical display and analysis of time series data. These new functions allow the user to identify a model, estimate the model parameters, and forecast future values of a univariate time-series by using ARIMA (or Box-Jenkins) models. Use of these functions provides rapid feedback about time-series data and fitted models. These functions make it easy to fit, check and compare ARIMA models.</p>
dc.identifier archive/lib.dr.iastate.edu/stat_las_preprints/4/
dc.identifier.articleid 1001
dc.identifier.contextkey 6968188
dc.identifier.s3bucket isulib-bepress-aws-west
dc.identifier.submissionpath stat_las_preprints/4
dc.identifier.uri https://dr.lib.iastate.edu/handle/20.500.12876/90332
dc.language.iso en
dc.source.bitstream archive/lib.dr.iastate.edu/stat_las_preprints/4/1995_08.pdf|||Fri Jan 14 23:59:20 UTC 2022
dc.subject.disciplines Statistics and Probability
dc.subject.keywords S-plus
dc.subject.keywords ARIMA model
dc.subject.keywords nonstationary time-series data
dc.subject.keywords identification
dc.subject.keywords estimation and diagnostic checking
dc.title Graphical Tools for Exploring and Analyzing Data From ARIMA Time Series Models
dc.type article
dc.type.genre article
dspace.entity.type Publication
relation.isAuthorOfPublication a1ae45d5-fca5-4709-bed9-3dd8efdba54e
relation.isOrgUnitOfPublication 264904d9-9e66-4169-8e11-034e537ddbca
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