In this paper, we propose nonparametric kernel estimators of the semivariogram, under the assumption of isotropy. At รฟrst, a symmetric kernel is considered in order to construct a consistent estimator, so that the selection of the bandwidth parameter is treated via the MSE or the MISE criteria. Next
A kernel-based method for nonparametric estimation of variograms
โ Scribed by Keming Yu; Jorge Mateu; Emilio Porcu
- Book ID
- 111014313
- Publisher
- John Wiley and Sons
- Year
- 2007
- Tongue
- English
- Weight
- 911 KB
- Volume
- 61
- Category
- Article
- ISSN
- 0039-0402
No coin nor oath required. For personal study only.
๐ SIMILAR VOLUMES
A conditional density function, which describes the relationship between response and explanatory variables, plays an important role in many analysis problems. In this paper, we propose a new kernelbased parametric method to estimate conditional density. An exponential function is employed to approx
for ordinary nonparametric kernel regression and for nonparametric generalized linear model kernel regression constructed estimators with lower order bias than the usual estimators, without the need for devices such as second derivative estimation and multiple bandwidths of different order. We deri
## Abstract In diseases caused by a deleterious gene mutation, knowledge of ageโspecific cumulative risks is necessary for medical management of mutation carriers. When pedigrees are ascertained through at least one affected individual, ascertainment bias can be corrected by using a parametric meth