A nonparametric method for benchmarking survey data via signal extraction / by Zhao-Guo Chen, Pierre A. Cholette and Estela Bee Dagum.: CS11-617/96-1E-PDF
"This paper compares two benchmarking methods, one based on regression modelling by Cholette and Dagum (1994) and the other based on ARIMA modelling signal extraction by Hillmer and Trabelsi (1987). The difficulties in the latter method of finding ARIMA models for the target series and the resulting implementation problems are discussed. A nonparametric approach to circumvent this problem is proposed, and more general models for estimating and benchmaking repeated survey data are introduced. Simulations show the proposed method and models are efficient and easy to implement"--Abstract.
Permanent link to this Catalogue record:
publications.gc.ca/pub?id=9.840283&sl=0
| Department/Agency |
|
|---|---|
| Title | A nonparametric method for benchmarking survey data via signal extraction / by Zhao-Guo Chen, Pierre A. Cholette and Estela Bee Dagum. |
| Series title |
|
| Publication type | Monograph - View Master Record |
| Language | [English] |
| Format | Digital text |
| Electronic document | |
| Note(s) |
|
| Publishing information |
|
| Author / Contributor |
|
| Description | 26 p. |
| Catalogue number |
|
| Departmental catalogue number | 11-617 no. 96-01 |
| Subject terms |
Request alternate formats
To request an alternate format of a publication, complete the Government of Canada Publications email form. Use the form’s “question or comment” field to specify the requested publication.Page details
- Date modified: