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Discrete Nonparametric Kernel and Parametric Methods for the Modeling of Pavement Deterioration
| Content Provider | Hyper Articles en Ligne (HAL) |
|---|---|
| Author | Senga Kiessé, Tristan Lorino, Tristan Khraibani, Hussein |
| Abstract | This article is concerned with one discrete nonparametric kernel and two parametric regression approaches for providing the evolution law of pavement deterioration. The first parametric approach is a survival data analysis method; and the second is a nonlinear mixed-effects model. The nonparametric approach consists of a regression estimator using the discrete associated kernels. Some asymptotic properties of the discrete nonparametric kernel estimator are shown as, in particular, its almost sure consistency. Moreover, two data-driven bandwidth selection methods are also given, with a new theoretical explicit expression of optimal bandwidth provided for this nonparametric estimator. A comparative simulation study is realized with an application of bootstrap methods to a measure of statistical accuracy. |
| Related Links | https://hal.science/hal-01097948/file/TSK2014c.pdf |
| ISSN | 03610926 |
| e-ISSN | 1532415X |
| DOI | 10.1080/03610926.2012.670355 |
| Issue Number | 6 |
| Volume Number | 43 |
| Conference Proceedings | Communications in Statistics - Theory and Methods |
| Language | English |
| Publisher | HAL CCSD Taylor & Francis |
| Publisher Date | 2014-03-04 |
| Access Restriction | Open |
| Subject Keyword | Nonparametric regression Bootstrap methods Discrete associated kernel Pavement design Survival data Nonlinear regression Mathematics [math] Statistics [math.ST] Mathematics [math] |
| Content Type | Text |
| Resource Type | Conference Proceedings |
| Subject | Statistics and Probability |
