Smoothing Techniques for the Bivariate Kaplan-Meier Estimator

Bae, Whasoo; Choi, Hyemi; Park, Byeong U.; Kim, Choongrak

doi:10.1081/sta-200063317

Cited by 6 publications

(6 citation statements)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Kim et al (2000) applied Bezier curve smoothing to the estimation of the measurement error model. Further use of the Bezier curve are the smoothing of the KaplanMeier estimator (Kim et al, 2003), the smoothing of the bivariate Kaplan-Meier estimator (Bae et al, 2005), the selection of Bezier points in density estimation and regression (Kim and Park, 2012) and the nonparametric estimation of distribution function using the Bezier curve (Bae et al, 2014). Note that the kernel smoothing has a poor performance at the boundary, especially in the survival function estimation.…”

Section: Introductionmentioning

confidence: 99%

Bezier curve smoothing of cumulative hazard function estimators

Cha

Kim

2016

CSAM

Self Cite

View full text Add to dashboard Cite

In survival analysis, the Nelson-Aalen estimator and Peterson estimator are often used to estimate a cumulative hazard function in randomly right censored data. In this paper, we suggested the smoothing version of the cumulative hazard function estimators using a Bezier curve. We compare them with the existing estimators including a kernel smooth version of the Nelson-Aalen estimator and the Peterson estimator in the sense of mean integrated square error to show through numerical studies that the proposed estimators are better than existing ones. Further, we applied our method to the Cox regression where covariates are used as predictors and suggested a survival function estimation at a given covariate.

show abstract

Section: Introductionmentioning

confidence: 99%

Bezier curve smoothing of cumulative hazard function estimators

Cha

Kim

2016

CSAM

Self Cite

View full text Add to dashboard Cite

show abstract

“…Subsequently, Kim et al (2000) applied Bezier curve smoothing to estimation in the measurement error model. Subsequent works of the Bezier curve are the smoothing of a Kaplan-Meier estimator (Kim et al, 2003), the smoothing of a bivariate Kaplan-Meier estimator (Bae et al, 2005), and the selection of Bezier points in density estimation and regression (Kim and Park, 2012).…”

Section: Introductionmentioning

confidence: 99%

Nonparametric Estimation of Distribution Function using Bezier Curve

Bae¹,

Kim²,

Kim³

2014

Communications for Statistical Applications and Methods

Self Cite

View full text Add to dashboard Cite

show abstract

“…Kim (1996) first applied the Bezier curve to density estimation in the statistical area and Kim et al (1999) showed that estimators using the Bezier curve smoothing in density estimation and regression function estimation have the same asymptotic properties as classical kernel estimators. Subsequent works on applications of the Bezier curve to statistics are the estimation in the measurement error model (Kim et al, 2000), the smoothing of the Kaplan-Meier estimator (Kim et al, 2003), and the smoothing of the bivariate Kaplan-Meier estimator (Bae et al, 2005).…”

Section: Introductionmentioning

confidence: 99%

On the Selection of Bezier Points in Bezier Curve Smoothing

Kim

Park²

2012

Korean Journal of Applied Statistics

Self Cite

View full text Add to dashboard Cite

Nonparametric methods are often used as an alternative to parametric methods to estimate density function and regression function. In this paper we consider improved methods to select the Bezier points in Bezier curve smoothing that is shown to have the same asymptotic properties as the kernel methods. We show that the proposed methods are better than the existing methods through numerical studies.

show abstract

Smoothing Techniques for the Bivariate Kaplan-Meier Estimator

Cited by 6 publications

References 7 publications

Bezier curve smoothing of cumulative hazard function estimators

Bezier curve smoothing of cumulative hazard function estimators

Nonparametric Estimation of Distribution Function using Bezier Curve

On the Selection of Bezier Points in Bezier Curve Smoothing

Contact Info

Product

Resources

About