Nonparametric Trend Analysis
| dc.contributor.author | Jose, C.T. | |
| dc.date.accessioned | 2014-07-08T04:45:39Z | |
| dc.date.available | 2014-07-08T04:45:39Z | |
| dc.date.issued | 2007-02 | |
| dc.description.abstract | The use of nonparametric techniques has a long tradition in time series analysis. Running mean, a very simple type of smoother has been used since the early 1900s for determining trends in time series. The increased data availability and the explosion of computing power have made it possible to use a wide range of other modern nonparametric techniques in time series analysis recently. The nonparametric estimation of trend and growth rate has been discussed in this paper. Kernel weighted linear regression method has been proposed to estimate the trend and growth rate nonparametrically. The method is applied to the data of area and production of arecanut in India. | en_US |
| dc.identifier.citation | Paper presented in the 54th Annual Conference of the Indian Society of Agricultural Statistics held at NDUAT Faizabad from 28-30 November 2000 | en_US |
| dc.identifier.uri | http://hdl.handle.net/123456789/3819 | |
| dc.language.iso | en | en_US |
| dc.title | Nonparametric Trend Analysis | en_US |
| dc.type | Article | en_US |