Expected Optimal Feedback with Time-Varying Parameters
In this paper we derive the closed loop form of the Expected Optimal Feedback rule, sometimes called passive learning stochastic control, with time varying parameters. As such this paper extends the work of Kendrick (Stochastic control for economic models, 1981 ; Stochastic control for economic mode...
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| Veröffentlicht in: | Computational economics 2013-10, Vol.42 (3), p.351-371 |
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| container_title | Computational economics |
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| creator | Tucci, Marco P. Kendrick, David A. Amman, Hans M. |
| description | In this paper we derive the closed loop form of the
Expected Optimal Feedback
rule, sometimes called passive learning stochastic control, with time varying parameters. As such this paper extends the work of Kendrick (Stochastic control for economic models,
1981
; Stochastic control for economic models,
2002
, Chap. 6) where parameters are assumed to vary randomly around a known constant mean. Furthermore, we show that the cautionary myopic rule in Beck and Wieland (J Econ Dyn Control 26:1359–1377,
2002
) model, a test bed for comparing various stochastic optimizations approaches, can be cast into this framework and can be treated as a special case of this solution. |
| doi_str_mv | 10.1007/s10614-012-9340-0 |
| format | Article |
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Expected Optimal Feedback
rule, sometimes called passive learning stochastic control, with time varying parameters. As such this paper extends the work of Kendrick (Stochastic control for economic models,
1981
; Stochastic control for economic models,
2002
, Chap. 6) where parameters are assumed to vary randomly around a known constant mean. Furthermore, we show that the cautionary myopic rule in Beck and Wieland (J Econ Dyn Control 26:1359–1377,
2002
) model, a test bed for comparing various stochastic optimizations approaches, can be cast into this framework and can be treated as a special case of this solution.</description><identifier>ISSN: 0927-7099</identifier><identifier>EISSN: 1572-9974</identifier><identifier>DOI: 10.1007/s10614-012-9340-0</identifier><language>eng</language><publisher>Boston: Springer US</publisher><subject>Approximation ; Behavioral/Experimental Economics ; Computational mathematics ; Computational methods ; Computer Appl. in Social and Behavioral Sciences ; Control theory ; Data analysis ; Econometrics ; Economic models ; Economic statistics ; Economic theory ; Economic Theory/Quantitative Economics/Mathematical Methods ; Economics ; Economics and Finance ; Kalman filters ; Markov analysis ; Math Applications in Computer Science ; Operations Research/Decision Theory ; Optimization ; Random sampling ; Stochastic models ; Studies ; Time series</subject><ispartof>Computational economics, 2013-10, Vol.42 (3), p.351-371</ispartof><rights>Springer Science+Business Media New York 2012</rights><rights>Springer Science+Business Media New York 2013</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c413t-657f4550ff1d3045aeb258f5ca1e8543cf5c5f0cc49738b614b1174a33c9a0f43</citedby><cites>FETCH-LOGICAL-c413t-657f4550ff1d3045aeb258f5ca1e8543cf5c5f0cc49738b614b1174a33c9a0f43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10614-012-9340-0$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10614-012-9340-0$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,41488,42557,51319</link.rule.ids></links><search><creatorcontrib>Tucci, Marco P.</creatorcontrib><creatorcontrib>Kendrick, David A.</creatorcontrib><creatorcontrib>Amman, Hans M.</creatorcontrib><title>Expected Optimal Feedback with Time-Varying Parameters</title><title>Computational economics</title><addtitle>Comput Econ</addtitle><description>In this paper we derive the closed loop form of the
Expected Optimal Feedback
rule, sometimes called passive learning stochastic control, with time varying parameters. As such this paper extends the work of Kendrick (Stochastic control for economic models,
1981
; Stochastic control for economic models,
2002
, Chap. 6) where parameters are assumed to vary randomly around a known constant mean. Furthermore, we show that the cautionary myopic rule in Beck and Wieland (J Econ Dyn Control 26:1359–1377,
2002
) model, a test bed for comparing various stochastic optimizations approaches, can be cast into this framework and can be treated as a special case of this solution.</description><subject>Approximation</subject><subject>Behavioral/Experimental Economics</subject><subject>Computational mathematics</subject><subject>Computational methods</subject><subject>Computer Appl. in Social and Behavioral Sciences</subject><subject>Control theory</subject><subject>Data analysis</subject><subject>Econometrics</subject><subject>Economic models</subject><subject>Economic statistics</subject><subject>Economic theory</subject><subject>Economic Theory/Quantitative Economics/Mathematical Methods</subject><subject>Economics</subject><subject>Economics and Finance</subject><subject>Kalman filters</subject><subject>Markov analysis</subject><subject>Math Applications in Computer Science</subject><subject>Operations Research/Decision Theory</subject><subject>Optimization</subject><subject>Random sampling</subject><subject>Stochastic models</subject><subject>Studies</subject><subject>Time series</subject><issn>0927-7099</issn><issn>1572-9974</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><recordid>eNp1kE9LAzEQxYMoWKsfwNuCFy_RySbZbI5SWhWEeqheQzadrVv3n8kW7bc3ZT2I4Glm4Pce8x4hlwxuGIC6DQwyJiiwlGougMIRmTCp4qWVOCYT0KmiCrQ-JWchbAFAsjSdkGz-1aMbcJ0s-6FqbJ0sENeFde_JZzW8JauqQfpq_b5qN8mz9bbBAX04JyelrQNe_MwpeVnMV7MH-rS8f5zdPVEnGB9oJlUppISyZGsOQlosUpmX0lmGuRTcxVWW4JzQiudFTFAwpoTl3GkLpeBTcj369r772GEYTFMFh3VtW-x2wTDBlZZ5LlVEr_6g227n2_jdgeKQKa5kpNhIOd-F4LE0vY-x_d4wMIcmzdikiU2aQ5MGoiYdNSGy7Qb9L-d_Rd8i6nPM</recordid><startdate>20131001</startdate><enddate>20131001</enddate><creator>Tucci, Marco P.</creator><creator>Kendrick, David A.</creator><creator>Amman, Hans M.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>0U~</scope><scope>1-H</scope><scope>3V.</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>8AO</scope><scope>8BJ</scope><scope>8FE</scope><scope>8FG</scope><scope>8FK</scope><scope>8FL</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FQK</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>JBE</scope><scope>JQ2</scope><scope>K60</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>L.0</scope><scope>M0C</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope></search><sort><creationdate>20131001</creationdate><title>Expected Optimal Feedback with Time-Varying Parameters</title><author>Tucci, Marco P. ; 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Expected Optimal Feedback
rule, sometimes called passive learning stochastic control, with time varying parameters. As such this paper extends the work of Kendrick (Stochastic control for economic models,
1981
; Stochastic control for economic models,
2002
, Chap. 6) where parameters are assumed to vary randomly around a known constant mean. Furthermore, we show that the cautionary myopic rule in Beck and Wieland (J Econ Dyn Control 26:1359–1377,
2002
) model, a test bed for comparing various stochastic optimizations approaches, can be cast into this framework and can be treated as a special case of this solution.</abstract><cop>Boston</cop><pub>Springer US</pub><doi>10.1007/s10614-012-9340-0</doi><tpages>21</tpages></addata></record> |
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| subjects | Approximation Behavioral/Experimental Economics Computational mathematics Computational methods Computer Appl. in Social and Behavioral Sciences Control theory Data analysis Econometrics Economic models Economic statistics Economic theory Economic Theory/Quantitative Economics/Mathematical Methods Economics Economics and Finance Kalman filters Markov analysis Math Applications in Computer Science Operations Research/Decision Theory Optimization Random sampling Stochastic models Studies Time series |
| title | Expected Optimal Feedback with Time-Varying Parameters |
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