Partial autocorrelation parameterization for subset autoregression
A new version of the partial autocorrelation plot and a new family of subset autoregressive models are introduced. A comprehensive approach to model identification, estimation and diagnostic checking is developed for these models. These models are better suited to efficient model building of high‐or...
Ausführliche Beschreibung
Autor*in: |
McLeod, A. I [verfasserIn] |
---|
Format: |
Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2006 |
---|
Rechteinformationen: |
Nutzungsrecht: © COPYRIGHT 2006 Blackwell Publishers Ltd. |
---|
Schlagwörter: |
AR model identification and diagnostic checks |
---|
Übergeordnetes Werk: |
Enthalten in: Journal of time series analysis - Oxford : Wiley-Blackwell, 1980, 27(2006), 4, Seite 599-612 |
---|---|
Übergeordnetes Werk: |
volume:27 ; year:2006 ; number:4 ; pages:599-612 |
Links: |
Volltext |
---|
DOI / URN: |
10.1111/j.1467-9892.2006.00481.x |
---|
Katalog-ID: |
OLC1985152673 |
---|
LEADER | 01000caa a2200265 4500 | ||
---|---|---|---|
001 | OLC1985152673 | ||
003 | DE-627 | ||
005 | 20220215181528.0 | ||
007 | tu | ||
008 | 161202s2006 xx ||||| 00| ||eng c | ||
024 | 7 | |a 10.1111/j.1467-9892.2006.00481.x |2 doi | |
028 | 5 | 2 | |a PQ20170206 |
035 | |a (DE-627)OLC1985152673 | ||
035 | |a (DE-599)GBVOLC1985152673 | ||
035 | |a (PRQ)14301-2ca0cdbbe0b21e288ad0da81b745be5a3bb30c830bd4142c6759041b7aff7fd00 | ||
035 | |a (KEY)0102813820060000027000400599partialautocorrelationparameterizationforsubsetaut | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
082 | 0 | 4 | |a 510 |q DNB |
084 | |a 31.73 |2 bkl | ||
100 | 1 | |a McLeod, A. I |e verfasserin |4 aut | |
245 | 1 | 0 | |a Partial autocorrelation parameterization for subset autoregression |
264 | 1 | |c 2006 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
338 | |a Band |b nc |2 rdacarrier | ||
520 | |a A new version of the partial autocorrelation plot and a new family of subset autoregressive models are introduced. A comprehensive approach to model identification, estimation and diagnostic checking is developed for these models. These models are better suited to efficient model building of high‐order autoregressions with long time series. Several illustrative examples are given. | ||
540 | |a Nutzungsrecht: © COPYRIGHT 2006 Blackwell Publishers Ltd. | ||
650 | 4 | |a monthly sunspot series | |
650 | 4 | |a long time series | |
650 | 4 | |a AR model identification and diagnostic checks | |
650 | 4 | |a partial autocorrelation plot | |
650 | 4 | |a seasonal or periodic time series | |
650 | 4 | |a forecasting | |
650 | 4 | |a Regression analysis | |
650 | 4 | |a Studies | |
650 | 4 | |a Time series | |
650 | 4 | |a Models | |
650 | 4 | |a 91B84 | |
650 | 4 | |a Statistics Theory | |
650 | 4 | |a 62M10 | |
650 | 4 | |a Mathematics | |
700 | 1 | |a Zhang, Y |4 oth | |
773 | 0 | 8 | |i Enthalten in |t Journal of time series analysis |d Oxford : Wiley-Blackwell, 1980 |g 27(2006), 4, Seite 599-612 |w (DE-627)130624454 |w (DE-600)796625-8 |w (DE-576)016130901 |x 0143-9782 |7 nnns |
773 | 1 | 8 | |g volume:27 |g year:2006 |g number:4 |g pages:599-612 |
856 | 4 | 1 | |u http://dx.doi.org/10.1111/j.1467-9892.2006.00481.x |3 Volltext |
856 | 4 | 2 | |u http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9892.2006.00481.x/abstract |
856 | 4 | 2 | |u http://econpapers.repec.org/article/blajtsera/v_3a27_3ay_3a2006_3ai_3a4_3ap_3a599-612.htm |
856 | 4 | 2 | |u http://search.proquest.com/docview/202932789 |
856 | 4 | 2 | |u http://arxiv.org/abs/1611.01370 |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_OLC | ||
912 | |a SSG-OLC-MAT | ||
912 | |a SSG-OLC-WIW | ||
912 | |a SSG-OPC-MAT | ||
912 | |a GBV_ILN_20 | ||
912 | |a GBV_ILN_21 | ||
912 | |a GBV_ILN_22 | ||
912 | |a GBV_ILN_24 | ||
912 | |a GBV_ILN_26 | ||
912 | |a GBV_ILN_40 | ||
912 | |a GBV_ILN_60 | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_100 | ||
912 | |a GBV_ILN_285 | ||
912 | |a GBV_ILN_2004 | ||
912 | |a GBV_ILN_2005 | ||
912 | |a GBV_ILN_2006 | ||
912 | |a GBV_ILN_2007 | ||
912 | |a GBV_ILN_2009 | ||
912 | |a GBV_ILN_2012 | ||
912 | |a GBV_ILN_2015 | ||
912 | |a GBV_ILN_2021 | ||
912 | |a GBV_ILN_4193 | ||
912 | |a GBV_ILN_4266 | ||
912 | |a GBV_ILN_4305 | ||
912 | |a GBV_ILN_4307 | ||
912 | |a GBV_ILN_4314 | ||
912 | |a GBV_ILN_4317 | ||
912 | |a GBV_ILN_4324 | ||
936 | b | k | |a 31.73 |q AVZ |
951 | |a AR | ||
952 | |d 27 |j 2006 |e 4 |h 599-612 |
author_variant |
a i m ai aim |
---|---|
matchkey_str |
article:01439782:2006----::ataatcreainaaeeiainosb |
hierarchy_sort_str |
2006 |
bklnumber |
31.73 |
publishDate |
2006 |
allfields |
10.1111/j.1467-9892.2006.00481.x doi PQ20170206 (DE-627)OLC1985152673 (DE-599)GBVOLC1985152673 (PRQ)14301-2ca0cdbbe0b21e288ad0da81b745be5a3bb30c830bd4142c6759041b7aff7fd00 (KEY)0102813820060000027000400599partialautocorrelationparameterizationforsubsetaut DE-627 ger DE-627 rakwb eng 510 DNB 31.73 bkl McLeod, A. I verfasserin aut Partial autocorrelation parameterization for subset autoregression 2006 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier A new version of the partial autocorrelation plot and a new family of subset autoregressive models are introduced. A comprehensive approach to model identification, estimation and diagnostic checking is developed for these models. These models are better suited to efficient model building of high‐order autoregressions with long time series. Several illustrative examples are given. Nutzungsrecht: © COPYRIGHT 2006 Blackwell Publishers Ltd. monthly sunspot series long time series AR model identification and diagnostic checks partial autocorrelation plot seasonal or periodic time series forecasting Regression analysis Studies Time series Models 91B84 Statistics Theory 62M10 Mathematics Zhang, Y oth Enthalten in Journal of time series analysis Oxford : Wiley-Blackwell, 1980 27(2006), 4, Seite 599-612 (DE-627)130624454 (DE-600)796625-8 (DE-576)016130901 0143-9782 nnns volume:27 year:2006 number:4 pages:599-612 http://dx.doi.org/10.1111/j.1467-9892.2006.00481.x Volltext http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9892.2006.00481.x/abstract http://econpapers.repec.org/article/blajtsera/v_3a27_3ay_3a2006_3ai_3a4_3ap_3a599-612.htm http://search.proquest.com/docview/202932789 http://arxiv.org/abs/1611.01370 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_20 GBV_ILN_21 GBV_ILN_22 GBV_ILN_24 GBV_ILN_26 GBV_ILN_40 GBV_ILN_60 GBV_ILN_70 GBV_ILN_100 GBV_ILN_285 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2012 GBV_ILN_2015 GBV_ILN_2021 GBV_ILN_4193 GBV_ILN_4266 GBV_ILN_4305 GBV_ILN_4307 GBV_ILN_4314 GBV_ILN_4317 GBV_ILN_4324 31.73 AVZ AR 27 2006 4 599-612 |
spelling |
10.1111/j.1467-9892.2006.00481.x doi PQ20170206 (DE-627)OLC1985152673 (DE-599)GBVOLC1985152673 (PRQ)14301-2ca0cdbbe0b21e288ad0da81b745be5a3bb30c830bd4142c6759041b7aff7fd00 (KEY)0102813820060000027000400599partialautocorrelationparameterizationforsubsetaut DE-627 ger DE-627 rakwb eng 510 DNB 31.73 bkl McLeod, A. I verfasserin aut Partial autocorrelation parameterization for subset autoregression 2006 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier A new version of the partial autocorrelation plot and a new family of subset autoregressive models are introduced. A comprehensive approach to model identification, estimation and diagnostic checking is developed for these models. These models are better suited to efficient model building of high‐order autoregressions with long time series. Several illustrative examples are given. Nutzungsrecht: © COPYRIGHT 2006 Blackwell Publishers Ltd. monthly sunspot series long time series AR model identification and diagnostic checks partial autocorrelation plot seasonal or periodic time series forecasting Regression analysis Studies Time series Models 91B84 Statistics Theory 62M10 Mathematics Zhang, Y oth Enthalten in Journal of time series analysis Oxford : Wiley-Blackwell, 1980 27(2006), 4, Seite 599-612 (DE-627)130624454 (DE-600)796625-8 (DE-576)016130901 0143-9782 nnns volume:27 year:2006 number:4 pages:599-612 http://dx.doi.org/10.1111/j.1467-9892.2006.00481.x Volltext http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9892.2006.00481.x/abstract http://econpapers.repec.org/article/blajtsera/v_3a27_3ay_3a2006_3ai_3a4_3ap_3a599-612.htm http://search.proquest.com/docview/202932789 http://arxiv.org/abs/1611.01370 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_20 GBV_ILN_21 GBV_ILN_22 GBV_ILN_24 GBV_ILN_26 GBV_ILN_40 GBV_ILN_60 GBV_ILN_70 GBV_ILN_100 GBV_ILN_285 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2012 GBV_ILN_2015 GBV_ILN_2021 GBV_ILN_4193 GBV_ILN_4266 GBV_ILN_4305 GBV_ILN_4307 GBV_ILN_4314 GBV_ILN_4317 GBV_ILN_4324 31.73 AVZ AR 27 2006 4 599-612 |
allfields_unstemmed |
10.1111/j.1467-9892.2006.00481.x doi PQ20170206 (DE-627)OLC1985152673 (DE-599)GBVOLC1985152673 (PRQ)14301-2ca0cdbbe0b21e288ad0da81b745be5a3bb30c830bd4142c6759041b7aff7fd00 (KEY)0102813820060000027000400599partialautocorrelationparameterizationforsubsetaut DE-627 ger DE-627 rakwb eng 510 DNB 31.73 bkl McLeod, A. I verfasserin aut Partial autocorrelation parameterization for subset autoregression 2006 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier A new version of the partial autocorrelation plot and a new family of subset autoregressive models are introduced. A comprehensive approach to model identification, estimation and diagnostic checking is developed for these models. These models are better suited to efficient model building of high‐order autoregressions with long time series. Several illustrative examples are given. Nutzungsrecht: © COPYRIGHT 2006 Blackwell Publishers Ltd. monthly sunspot series long time series AR model identification and diagnostic checks partial autocorrelation plot seasonal or periodic time series forecasting Regression analysis Studies Time series Models 91B84 Statistics Theory 62M10 Mathematics Zhang, Y oth Enthalten in Journal of time series analysis Oxford : Wiley-Blackwell, 1980 27(2006), 4, Seite 599-612 (DE-627)130624454 (DE-600)796625-8 (DE-576)016130901 0143-9782 nnns volume:27 year:2006 number:4 pages:599-612 http://dx.doi.org/10.1111/j.1467-9892.2006.00481.x Volltext http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9892.2006.00481.x/abstract http://econpapers.repec.org/article/blajtsera/v_3a27_3ay_3a2006_3ai_3a4_3ap_3a599-612.htm http://search.proquest.com/docview/202932789 http://arxiv.org/abs/1611.01370 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_20 GBV_ILN_21 GBV_ILN_22 GBV_ILN_24 GBV_ILN_26 GBV_ILN_40 GBV_ILN_60 GBV_ILN_70 GBV_ILN_100 GBV_ILN_285 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2012 GBV_ILN_2015 GBV_ILN_2021 GBV_ILN_4193 GBV_ILN_4266 GBV_ILN_4305 GBV_ILN_4307 GBV_ILN_4314 GBV_ILN_4317 GBV_ILN_4324 31.73 AVZ AR 27 2006 4 599-612 |
allfieldsGer |
10.1111/j.1467-9892.2006.00481.x doi PQ20170206 (DE-627)OLC1985152673 (DE-599)GBVOLC1985152673 (PRQ)14301-2ca0cdbbe0b21e288ad0da81b745be5a3bb30c830bd4142c6759041b7aff7fd00 (KEY)0102813820060000027000400599partialautocorrelationparameterizationforsubsetaut DE-627 ger DE-627 rakwb eng 510 DNB 31.73 bkl McLeod, A. I verfasserin aut Partial autocorrelation parameterization for subset autoregression 2006 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier A new version of the partial autocorrelation plot and a new family of subset autoregressive models are introduced. A comprehensive approach to model identification, estimation and diagnostic checking is developed for these models. These models are better suited to efficient model building of high‐order autoregressions with long time series. Several illustrative examples are given. Nutzungsrecht: © COPYRIGHT 2006 Blackwell Publishers Ltd. monthly sunspot series long time series AR model identification and diagnostic checks partial autocorrelation plot seasonal or periodic time series forecasting Regression analysis Studies Time series Models 91B84 Statistics Theory 62M10 Mathematics Zhang, Y oth Enthalten in Journal of time series analysis Oxford : Wiley-Blackwell, 1980 27(2006), 4, Seite 599-612 (DE-627)130624454 (DE-600)796625-8 (DE-576)016130901 0143-9782 nnns volume:27 year:2006 number:4 pages:599-612 http://dx.doi.org/10.1111/j.1467-9892.2006.00481.x Volltext http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9892.2006.00481.x/abstract http://econpapers.repec.org/article/blajtsera/v_3a27_3ay_3a2006_3ai_3a4_3ap_3a599-612.htm http://search.proquest.com/docview/202932789 http://arxiv.org/abs/1611.01370 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_20 GBV_ILN_21 GBV_ILN_22 GBV_ILN_24 GBV_ILN_26 GBV_ILN_40 GBV_ILN_60 GBV_ILN_70 GBV_ILN_100 GBV_ILN_285 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2012 GBV_ILN_2015 GBV_ILN_2021 GBV_ILN_4193 GBV_ILN_4266 GBV_ILN_4305 GBV_ILN_4307 GBV_ILN_4314 GBV_ILN_4317 GBV_ILN_4324 31.73 AVZ AR 27 2006 4 599-612 |
allfieldsSound |
10.1111/j.1467-9892.2006.00481.x doi PQ20170206 (DE-627)OLC1985152673 (DE-599)GBVOLC1985152673 (PRQ)14301-2ca0cdbbe0b21e288ad0da81b745be5a3bb30c830bd4142c6759041b7aff7fd00 (KEY)0102813820060000027000400599partialautocorrelationparameterizationforsubsetaut DE-627 ger DE-627 rakwb eng 510 DNB 31.73 bkl McLeod, A. I verfasserin aut Partial autocorrelation parameterization for subset autoregression 2006 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier A new version of the partial autocorrelation plot and a new family of subset autoregressive models are introduced. A comprehensive approach to model identification, estimation and diagnostic checking is developed for these models. These models are better suited to efficient model building of high‐order autoregressions with long time series. Several illustrative examples are given. Nutzungsrecht: © COPYRIGHT 2006 Blackwell Publishers Ltd. monthly sunspot series long time series AR model identification and diagnostic checks partial autocorrelation plot seasonal or periodic time series forecasting Regression analysis Studies Time series Models 91B84 Statistics Theory 62M10 Mathematics Zhang, Y oth Enthalten in Journal of time series analysis Oxford : Wiley-Blackwell, 1980 27(2006), 4, Seite 599-612 (DE-627)130624454 (DE-600)796625-8 (DE-576)016130901 0143-9782 nnns volume:27 year:2006 number:4 pages:599-612 http://dx.doi.org/10.1111/j.1467-9892.2006.00481.x Volltext http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9892.2006.00481.x/abstract http://econpapers.repec.org/article/blajtsera/v_3a27_3ay_3a2006_3ai_3a4_3ap_3a599-612.htm http://search.proquest.com/docview/202932789 http://arxiv.org/abs/1611.01370 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_20 GBV_ILN_21 GBV_ILN_22 GBV_ILN_24 GBV_ILN_26 GBV_ILN_40 GBV_ILN_60 GBV_ILN_70 GBV_ILN_100 GBV_ILN_285 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2012 GBV_ILN_2015 GBV_ILN_2021 GBV_ILN_4193 GBV_ILN_4266 GBV_ILN_4305 GBV_ILN_4307 GBV_ILN_4314 GBV_ILN_4317 GBV_ILN_4324 31.73 AVZ AR 27 2006 4 599-612 |
language |
English |
source |
Enthalten in Journal of time series analysis 27(2006), 4, Seite 599-612 volume:27 year:2006 number:4 pages:599-612 |
sourceStr |
Enthalten in Journal of time series analysis 27(2006), 4, Seite 599-612 volume:27 year:2006 number:4 pages:599-612 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
monthly sunspot series long time series AR model identification and diagnostic checks partial autocorrelation plot seasonal or periodic time series forecasting Regression analysis Studies Time series Models 91B84 Statistics Theory 62M10 Mathematics |
dewey-raw |
510 |
isfreeaccess_bool |
false |
container_title |
Journal of time series analysis |
authorswithroles_txt_mv |
McLeod, A. I @@aut@@ Zhang, Y @@oth@@ |
publishDateDaySort_date |
2006-01-01T00:00:00Z |
hierarchy_top_id |
130624454 |
dewey-sort |
3510 |
id |
OLC1985152673 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1985152673</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220215181528.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">161202s2006 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1111/j.1467-9892.2006.00481.x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20170206</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1985152673</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1985152673</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)14301-2ca0cdbbe0b21e288ad0da81b745be5a3bb30c830bd4142c6759041b7aff7fd00</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0102813820060000027000400599partialautocorrelationparameterizationforsubsetaut</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">31.73</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">McLeod, A. I</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Partial autocorrelation parameterization for subset autoregression</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2006</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">A new version of the partial autocorrelation plot and a new family of subset autoregressive models are introduced. A comprehensive approach to model identification, estimation and diagnostic checking is developed for these models. These models are better suited to efficient model building of high‐order autoregressions with long time series. Several illustrative examples are given.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">Nutzungsrecht: © COPYRIGHT 2006 Blackwell Publishers Ltd.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">monthly sunspot series</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">long time series</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">AR model identification and diagnostic checks</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">partial autocorrelation plot</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">seasonal or periodic time series</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">forecasting</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Regression analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Studies</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Time series</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Models</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">91B84</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistics Theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">62M10</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematics</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, Y</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of time series analysis</subfield><subfield code="d">Oxford : Wiley-Blackwell, 1980</subfield><subfield code="g">27(2006), 4, Seite 599-612</subfield><subfield code="w">(DE-627)130624454</subfield><subfield code="w">(DE-600)796625-8</subfield><subfield code="w">(DE-576)016130901</subfield><subfield code="x">0143-9782</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:27</subfield><subfield code="g">year:2006</subfield><subfield code="g">number:4</subfield><subfield code="g">pages:599-612</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1111/j.1467-9892.2006.00481.x</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9892.2006.00481.x/abstract</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://econpapers.repec.org/article/blajtsera/v_3a27_3ay_3a2006_3ai_3a4_3ap_3a599-612.htm</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://search.proquest.com/docview/202932789</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://arxiv.org/abs/1611.01370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-WIW</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_21</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_26</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2007</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4193</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4266</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4314</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4317</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">31.73</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">27</subfield><subfield code="j">2006</subfield><subfield code="e">4</subfield><subfield code="h">599-612</subfield></datafield></record></collection>
|
author |
McLeod, A. I |
spellingShingle |
McLeod, A. I ddc 510 bkl 31.73 misc monthly sunspot series misc long time series misc AR model identification and diagnostic checks misc partial autocorrelation plot misc seasonal or periodic time series misc forecasting misc Regression analysis misc Studies misc Time series misc Models misc 91B84 misc Statistics Theory misc 62M10 misc Mathematics Partial autocorrelation parameterization for subset autoregression |
authorStr |
McLeod, A. I |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)130624454 |
format |
Article |
dewey-ones |
510 - Mathematics |
delete_txt_mv |
keep |
author_role |
aut |
collection |
OLC |
remote_str |
false |
illustrated |
Not Illustrated |
issn |
0143-9782 |
topic_title |
510 DNB 31.73 bkl Partial autocorrelation parameterization for subset autoregression monthly sunspot series long time series AR model identification and diagnostic checks partial autocorrelation plot seasonal or periodic time series forecasting Regression analysis Studies Time series Models 91B84 Statistics Theory 62M10 Mathematics |
topic |
ddc 510 bkl 31.73 misc monthly sunspot series misc long time series misc AR model identification and diagnostic checks misc partial autocorrelation plot misc seasonal or periodic time series misc forecasting misc Regression analysis misc Studies misc Time series misc Models misc 91B84 misc Statistics Theory misc 62M10 misc Mathematics |
topic_unstemmed |
ddc 510 bkl 31.73 misc monthly sunspot series misc long time series misc AR model identification and diagnostic checks misc partial autocorrelation plot misc seasonal or periodic time series misc forecasting misc Regression analysis misc Studies misc Time series misc Models misc 91B84 misc Statistics Theory misc 62M10 misc Mathematics |
topic_browse |
ddc 510 bkl 31.73 misc monthly sunspot series misc long time series misc AR model identification and diagnostic checks misc partial autocorrelation plot misc seasonal or periodic time series misc forecasting misc Regression analysis misc Studies misc Time series misc Models misc 91B84 misc Statistics Theory misc 62M10 misc Mathematics |
format_facet |
Aufsätze Gedruckte Aufsätze |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
nc |
author2_variant |
y z yz |
hierarchy_parent_title |
Journal of time series analysis |
hierarchy_parent_id |
130624454 |
dewey-tens |
510 - Mathematics |
hierarchy_top_title |
Journal of time series analysis |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)130624454 (DE-600)796625-8 (DE-576)016130901 |
title |
Partial autocorrelation parameterization for subset autoregression |
ctrlnum |
(DE-627)OLC1985152673 (DE-599)GBVOLC1985152673 (PRQ)14301-2ca0cdbbe0b21e288ad0da81b745be5a3bb30c830bd4142c6759041b7aff7fd00 (KEY)0102813820060000027000400599partialautocorrelationparameterizationforsubsetaut |
title_full |
Partial autocorrelation parameterization for subset autoregression |
author_sort |
McLeod, A. I |
journal |
Journal of time series analysis |
journalStr |
Journal of time series analysis |
lang_code |
eng |
isOA_bool |
false |
dewey-hundreds |
500 - Science |
recordtype |
marc |
publishDateSort |
2006 |
contenttype_str_mv |
txt |
container_start_page |
599 |
author_browse |
McLeod, A. I |
container_volume |
27 |
class |
510 DNB 31.73 bkl |
format_se |
Aufsätze |
author-letter |
McLeod, A. I |
doi_str_mv |
10.1111/j.1467-9892.2006.00481.x |
dewey-full |
510 |
title_sort |
partial autocorrelation parameterization for subset autoregression |
title_auth |
Partial autocorrelation parameterization for subset autoregression |
abstract |
A new version of the partial autocorrelation plot and a new family of subset autoregressive models are introduced. A comprehensive approach to model identification, estimation and diagnostic checking is developed for these models. These models are better suited to efficient model building of high‐order autoregressions with long time series. Several illustrative examples are given. |
abstractGer |
A new version of the partial autocorrelation plot and a new family of subset autoregressive models are introduced. A comprehensive approach to model identification, estimation and diagnostic checking is developed for these models. These models are better suited to efficient model building of high‐order autoregressions with long time series. Several illustrative examples are given. |
abstract_unstemmed |
A new version of the partial autocorrelation plot and a new family of subset autoregressive models are introduced. A comprehensive approach to model identification, estimation and diagnostic checking is developed for these models. These models are better suited to efficient model building of high‐order autoregressions with long time series. Several illustrative examples are given. |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-MAT SSG-OLC-WIW SSG-OPC-MAT GBV_ILN_20 GBV_ILN_21 GBV_ILN_22 GBV_ILN_24 GBV_ILN_26 GBV_ILN_40 GBV_ILN_60 GBV_ILN_70 GBV_ILN_100 GBV_ILN_285 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2009 GBV_ILN_2012 GBV_ILN_2015 GBV_ILN_2021 GBV_ILN_4193 GBV_ILN_4266 GBV_ILN_4305 GBV_ILN_4307 GBV_ILN_4314 GBV_ILN_4317 GBV_ILN_4324 |
container_issue |
4 |
title_short |
Partial autocorrelation parameterization for subset autoregression |
url |
http://dx.doi.org/10.1111/j.1467-9892.2006.00481.x http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9892.2006.00481.x/abstract http://econpapers.repec.org/article/blajtsera/v_3a27_3ay_3a2006_3ai_3a4_3ap_3a599-612.htm http://search.proquest.com/docview/202932789 http://arxiv.org/abs/1611.01370 |
remote_bool |
false |
author2 |
Zhang, Y |
author2Str |
Zhang, Y |
ppnlink |
130624454 |
mediatype_str_mv |
n |
isOA_txt |
false |
hochschulschrift_bool |
false |
author2_role |
oth |
doi_str |
10.1111/j.1467-9892.2006.00481.x |
up_date |
2024-07-04T02:22:11.418Z |
_version_ |
1803613352933457920 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1985152673</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20220215181528.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">161202s2006 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1111/j.1467-9892.2006.00481.x</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20170206</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1985152673</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1985152673</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)14301-2ca0cdbbe0b21e288ad0da81b745be5a3bb30c830bd4142c6759041b7aff7fd00</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0102813820060000027000400599partialautocorrelationparameterizationforsubsetaut</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">510</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="084" ind1=" " ind2=" "><subfield code="a">31.73</subfield><subfield code="2">bkl</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">McLeod, A. I</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Partial autocorrelation parameterization for subset autoregression</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2006</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">A new version of the partial autocorrelation plot and a new family of subset autoregressive models are introduced. A comprehensive approach to model identification, estimation and diagnostic checking is developed for these models. These models are better suited to efficient model building of high‐order autoregressions with long time series. Several illustrative examples are given.</subfield></datafield><datafield tag="540" ind1=" " ind2=" "><subfield code="a">Nutzungsrecht: © COPYRIGHT 2006 Blackwell Publishers Ltd.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">monthly sunspot series</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">long time series</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">AR model identification and diagnostic checks</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">partial autocorrelation plot</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">seasonal or periodic time series</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">forecasting</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Regression analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Studies</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Time series</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Models</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">91B84</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Statistics Theory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">62M10</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematics</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhang, Y</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">Journal of time series analysis</subfield><subfield code="d">Oxford : Wiley-Blackwell, 1980</subfield><subfield code="g">27(2006), 4, Seite 599-612</subfield><subfield code="w">(DE-627)130624454</subfield><subfield code="w">(DE-600)796625-8</subfield><subfield code="w">(DE-576)016130901</subfield><subfield code="x">0143-9782</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:27</subfield><subfield code="g">year:2006</subfield><subfield code="g">number:4</subfield><subfield code="g">pages:599-612</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1111/j.1467-9892.2006.00481.x</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://onlinelibrary.wiley.com/doi/10.1111/j.1467-9892.2006.00481.x/abstract</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://econpapers.repec.org/article/blajtsera/v_3a27_3ay_3a2006_3ai_3a4_3ap_3a599-612.htm</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://search.proquest.com/docview/202932789</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://arxiv.org/abs/1611.01370</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-WIW</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OPC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_20</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_21</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_22</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_24</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_26</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_40</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_60</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_100</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_285</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2005</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2006</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2007</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2009</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2012</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2015</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2021</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4193</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4266</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4305</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4307</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4314</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4317</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4324</subfield></datafield><datafield tag="936" ind1="b" ind2="k"><subfield code="a">31.73</subfield><subfield code="q">AVZ</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">27</subfield><subfield code="j">2006</subfield><subfield code="e">4</subfield><subfield code="h">599-612</subfield></datafield></record></collection>
|
score |
7.4013615 |