Abstract: Asymptotically exact and conservative confidence bands are obtained for non-parametric regression function, using piecewise constant and piecewise linear spline estimation, respectively. Compared to the pointwise confidence interval of Huang (2003), the confidence bands are inflated by a factor of {log (n)}1/2, with the same width order as the Nadaraya-Watson bands of Härdle (1989), the local polynomial bands of Xia (1998) and Claeskens and Van Keilegom (2003). Simulation experiments provide strong evidence that corroborates with the asymptotic theory. The linear spline bands has been applied to identify an appropriate polynomial trend for fossil data
Considerable attention has been directed in the statistical literature towards the construction of c...
The quality of an approximating function using measured data may be characterized by the magnitude o...
Considerable attention has been directed in the statistical literature towards the construction of c...
Asymptotically exact and conservative confidence bands are obtained for nonparametric re-gression fu...
Confidence bands for regression curves and their first p derivatives are obtained via local p-th ord...
Confidence bands for regression curves and their first p derivatives are obtained via local p-th ord...
This thesis deals with the constructions of the confidence band for a linear regression model. Basic...
In this article we construct simultaneous confidence bands for a smooth curve using penalized spline...
In this article we construct simultaneous confidence bands for a smooth curve using penalized spline...
Confidence bands for regression curves and their first p derivatives are obtained via local pth orde...
In this paper we construct simultaneous confidence bands for a smooth curve using penalized spline e...
In this paper we construct simultaneous confidence bands for a smooth curve using penalized spline e...
In this paper we construct simultaneous confidence bands for a smooth curve using penalized spline e...
We consider nonparametric estimation of coefficient functions in a varying coefficient model of the ...
Abstract: Functional data analysis has received considerable recent attention and a number of succes...
Considerable attention has been directed in the statistical literature towards the construction of c...
The quality of an approximating function using measured data may be characterized by the magnitude o...
Considerable attention has been directed in the statistical literature towards the construction of c...
Asymptotically exact and conservative confidence bands are obtained for nonparametric re-gression fu...
Confidence bands for regression curves and their first p derivatives are obtained via local p-th ord...
Confidence bands for regression curves and their first p derivatives are obtained via local p-th ord...
This thesis deals with the constructions of the confidence band for a linear regression model. Basic...
In this article we construct simultaneous confidence bands for a smooth curve using penalized spline...
In this article we construct simultaneous confidence bands for a smooth curve using penalized spline...
Confidence bands for regression curves and their first p derivatives are obtained via local pth orde...
In this paper we construct simultaneous confidence bands for a smooth curve using penalized spline e...
In this paper we construct simultaneous confidence bands for a smooth curve using penalized spline e...
In this paper we construct simultaneous confidence bands for a smooth curve using penalized spline e...
We consider nonparametric estimation of coefficient functions in a varying coefficient model of the ...
Abstract: Functional data analysis has received considerable recent attention and a number of succes...
Considerable attention has been directed in the statistical literature towards the construction of c...
The quality of an approximating function using measured data may be characterized by the magnitude o...
Considerable attention has been directed in the statistical literature towards the construction of c...