Logistic models with regime switching: Permanence and ergodicity
Focusing on stochastic dynamics involving continuous states as well as discrete events, this paper investigates stochastic logistic model with regime switching and obtains sufficient conditions for stochastic permanence, which are much weaker than the existing results in the literature. Furthermore,...
Ausführliche Beschreibung
Autor*in: |
Li, Xiaoyue [verfasserIn] |
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Format: |
E-Artikel |
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Sprache: |
Englisch |
Erschienen: |
2016 |
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Schlagwörter: |
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Umfang: |
19 |
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Übergeordnetes Werk: |
Enthalten in: In silico drug repurposing in COVID-19: A network-based analysis - Sibilio, Pasquale ELSEVIER, 2021, Amsterdam [u.a.] |
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Übergeordnetes Werk: |
volume:441 ; year:2016 ; number:2 ; day:15 ; month:09 ; pages:593-611 ; extent:19 |
Links: |
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DOI / URN: |
10.1016/j.jmaa.2016.04.016 |
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ELV019870574 |
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520 | |a Focusing on stochastic dynamics involving continuous states as well as discrete events, this paper investigates stochastic logistic model with regime switching and obtains sufficient conditions for stochastic permanence, which are much weaker than the existing results in the literature. Furthermore, under the conditions of stochastic permanence, the existence and uniqueness of stationary distribution is proved. An interesting fact is: The regime switching can suppress the non-permanence. A couple of examples and numerical simulations are given to illustrate our results. | ||
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10.1016/j.jmaa.2016.04.016 doi GBVA2016022000018.pica (DE-627)ELV019870574 (ELSEVIER)S0022-247X(16)30054-3 DE-627 ger DE-627 rakwb eng 510 510 DE-600 610 VZ 44.40 bkl Li, Xiaoyue verfasserin aut Logistic models with regime switching: Permanence and ergodicity 2016 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Focusing on stochastic dynamics involving continuous states as well as discrete events, this paper investigates stochastic logistic model with regime switching and obtains sufficient conditions for stochastic permanence, which are much weaker than the existing results in the literature. Furthermore, under the conditions of stochastic permanence, the existence and uniqueness of stationary distribution is proved. An interesting fact is: The regime switching can suppress the non-permanence. A couple of examples and numerical simulations are given to illustrate our results. Markov chain Elsevier Positive recurrence Elsevier Stochastic permanence Elsevier Stochastic logistic model Elsevier Stationary distribution Elsevier Yin, George oth Enthalten in Elsevier Sibilio, Pasquale ELSEVIER In silico drug repurposing in COVID-19: A network-based analysis 2021 Amsterdam [u.a.] (DE-627)ELV006634001 volume:441 year:2016 number:2 day:15 month:09 pages:593-611 extent:19 https://doi.org/10.1016/j.jmaa.2016.04.016 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 441 2016 2 15 0915 593-611 19 045F 510 |
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10.1016/j.jmaa.2016.04.016 doi GBVA2016022000018.pica (DE-627)ELV019870574 (ELSEVIER)S0022-247X(16)30054-3 DE-627 ger DE-627 rakwb eng 510 510 DE-600 610 VZ 44.40 bkl Li, Xiaoyue verfasserin aut Logistic models with regime switching: Permanence and ergodicity 2016 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Focusing on stochastic dynamics involving continuous states as well as discrete events, this paper investigates stochastic logistic model with regime switching and obtains sufficient conditions for stochastic permanence, which are much weaker than the existing results in the literature. Furthermore, under the conditions of stochastic permanence, the existence and uniqueness of stationary distribution is proved. An interesting fact is: The regime switching can suppress the non-permanence. A couple of examples and numerical simulations are given to illustrate our results. Markov chain Elsevier Positive recurrence Elsevier Stochastic permanence Elsevier Stochastic logistic model Elsevier Stationary distribution Elsevier Yin, George oth Enthalten in Elsevier Sibilio, Pasquale ELSEVIER In silico drug repurposing in COVID-19: A network-based analysis 2021 Amsterdam [u.a.] (DE-627)ELV006634001 volume:441 year:2016 number:2 day:15 month:09 pages:593-611 extent:19 https://doi.org/10.1016/j.jmaa.2016.04.016 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 441 2016 2 15 0915 593-611 19 045F 510 |
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10.1016/j.jmaa.2016.04.016 doi GBVA2016022000018.pica (DE-627)ELV019870574 (ELSEVIER)S0022-247X(16)30054-3 DE-627 ger DE-627 rakwb eng 510 510 DE-600 610 VZ 44.40 bkl Li, Xiaoyue verfasserin aut Logistic models with regime switching: Permanence and ergodicity 2016 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Focusing on stochastic dynamics involving continuous states as well as discrete events, this paper investigates stochastic logistic model with regime switching and obtains sufficient conditions for stochastic permanence, which are much weaker than the existing results in the literature. Furthermore, under the conditions of stochastic permanence, the existence and uniqueness of stationary distribution is proved. An interesting fact is: The regime switching can suppress the non-permanence. A couple of examples and numerical simulations are given to illustrate our results. Markov chain Elsevier Positive recurrence Elsevier Stochastic permanence Elsevier Stochastic logistic model Elsevier Stationary distribution Elsevier Yin, George oth Enthalten in Elsevier Sibilio, Pasquale ELSEVIER In silico drug repurposing in COVID-19: A network-based analysis 2021 Amsterdam [u.a.] (DE-627)ELV006634001 volume:441 year:2016 number:2 day:15 month:09 pages:593-611 extent:19 https://doi.org/10.1016/j.jmaa.2016.04.016 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 441 2016 2 15 0915 593-611 19 045F 510 |
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10.1016/j.jmaa.2016.04.016 doi GBVA2016022000018.pica (DE-627)ELV019870574 (ELSEVIER)S0022-247X(16)30054-3 DE-627 ger DE-627 rakwb eng 510 510 DE-600 610 VZ 44.40 bkl Li, Xiaoyue verfasserin aut Logistic models with regime switching: Permanence and ergodicity 2016 19 nicht spezifiziert zzz rdacontent nicht spezifiziert z rdamedia nicht spezifiziert zu rdacarrier Focusing on stochastic dynamics involving continuous states as well as discrete events, this paper investigates stochastic logistic model with regime switching and obtains sufficient conditions for stochastic permanence, which are much weaker than the existing results in the literature. Furthermore, under the conditions of stochastic permanence, the existence and uniqueness of stationary distribution is proved. An interesting fact is: The regime switching can suppress the non-permanence. A couple of examples and numerical simulations are given to illustrate our results. Markov chain Elsevier Positive recurrence Elsevier Stochastic permanence Elsevier Stochastic logistic model Elsevier Stationary distribution Elsevier Yin, George oth Enthalten in Elsevier Sibilio, Pasquale ELSEVIER In silico drug repurposing in COVID-19: A network-based analysis 2021 Amsterdam [u.a.] (DE-627)ELV006634001 volume:441 year:2016 number:2 day:15 month:09 pages:593-611 extent:19 https://doi.org/10.1016/j.jmaa.2016.04.016 Volltext GBV_USEFLAG_U GBV_ELV SYSFLAG_U SSG-OLC-PHA SSG-OPC-PHA 44.40 Pharmazie Pharmazeutika VZ AR 441 2016 2 15 0915 593-611 19 045F 510 |
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abstract |
Focusing on stochastic dynamics involving continuous states as well as discrete events, this paper investigates stochastic logistic model with regime switching and obtains sufficient conditions for stochastic permanence, which are much weaker than the existing results in the literature. Furthermore, under the conditions of stochastic permanence, the existence and uniqueness of stationary distribution is proved. An interesting fact is: The regime switching can suppress the non-permanence. A couple of examples and numerical simulations are given to illustrate our results. |
abstractGer |
Focusing on stochastic dynamics involving continuous states as well as discrete events, this paper investigates stochastic logistic model with regime switching and obtains sufficient conditions for stochastic permanence, which are much weaker than the existing results in the literature. Furthermore, under the conditions of stochastic permanence, the existence and uniqueness of stationary distribution is proved. An interesting fact is: The regime switching can suppress the non-permanence. A couple of examples and numerical simulations are given to illustrate our results. |
abstract_unstemmed |
Focusing on stochastic dynamics involving continuous states as well as discrete events, this paper investigates stochastic logistic model with regime switching and obtains sufficient conditions for stochastic permanence, which are much weaker than the existing results in the literature. Furthermore, under the conditions of stochastic permanence, the existence and uniqueness of stationary distribution is proved. An interesting fact is: The regime switching can suppress the non-permanence. A couple of examples and numerical simulations are given to illustrate our results. |
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