KRISHI
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http://krishi.icar.gov.in/jspui/handle/123456789/44666Full metadata record
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Krishna Pada Sarkar | en_US |
| dc.contributor.author | K. N. Singh | en_US |
| dc.contributor.author | Achal Lama | en_US |
| dc.contributor.author | Bishal Gurung | en_US |
| dc.date.accessioned | 2021-01-11T09:40:01Z | - |
| dc.date.available | 2021-01-11T09:40:01Z | - |
| dc.date.issued | 2020-10-01 | - |
| dc.identifier.citation | Not Available | en_US |
| dc.identifier.issn | Not Available | - |
| dc.identifier.uri | http://krishi.icar.gov.in/jspui/handle/123456789/44666 | - |
| dc.description | Not Available | en_US |
| dc.description.abstract | In the present study exogenous variable is incorporated in the long memory model to give better forecast of time series. Autoregressive Fractionally Integrated Moving Average- Generalized Autoregressive Conditional Heteroscedastic (ARFIMA-GARCH) and Autoregressive Fractionally Integrated Moving Average with exogenous variable- Generalized Autoregressive Conditional Heteroscedastic (ARFIMAX-GARCH) models are studied for describing the volatile data. Brief description of the models are given along with parameter estimation procedure. As an illustration daily minimum market price of onion along with daily market arrival of Lasalgaon market of Maharashtra, India is taken. Comparative study of the fitted model is carried out by calculating the Root Mean Square Error (RMSE) and Relative Mean Absolute Percentage Error (RMAPE) from the validation set. The superior performance of the ARFIMAX-GARCH model than ARFIMA-GARCH model is demonstrated for data under study | en_US |
| dc.description.sponsorship | Not Available | en_US |
| dc.language.iso | English | en_US |
| dc.publisher | Not Available | en_US |
| dc.relation.ispartofseries | Not Available; | - |
| dc.subject | Long memory | en_US |
| dc.subject | ARFIMA | en_US |
| dc.subject | ARFIMAX | en_US |
| dc.subject | ARFIMAX-GARCH | en_US |
| dc.subject | Forecasting | en_US |
| dc.title | Incorporation of Exogenous Variable in Long Memory Model: An ARFIMAX-GARCH Framework | en_US |
| dc.title.alternative | Not Available | en_US |
| dc.type | Research Paper | en_US |
| dc.publication.projectcode | Not Available | en_US |
| dc.publication.journalname | Journal of the Indian Society of Agricultural Statistics | en_US |
| dc.publication.volumeno | 74(2) | en_US |
| dc.publication.pagenumber | 99-106 | en_US |
| dc.publication.divisionUnit | Not Available | en_US |
| dc.publication.sourceUrl | Not Available | en_US |
| dc.publication.authorAffiliation | ICAR::Indian Agricultural Statistics Research Institute | en_US |
| dc.ICARdataUseLicence | http://krishi.icar.gov.in/PDF/ICAR_Data_Use_Licence.pdf | en_US |
| dc.publication.naasrating | 5.51 | - |
| Appears in Collections: | AEdu-IASRI-Publication | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 2-Krishna.pdf | 782.11 kB | Adobe PDF | View/Open |
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