Nonparametric estimation of density derivatives of dependent data

✍ Scribed by Alejandro Quintela del Ríoz

• Publisher: Elsevier Science
• Year: 1997
• Tongue: English
• Weight: 742 KB
• Volume: 61
• Category: Article
• ISSN: 0378-3758
• DOI: 10.1016/s0378-3758(96)00141-3

✦ Synopsis

We study here the kernel type, nonparametric estimation of the derivatives of the density function associated with a strongly mixing time series. The consistency and asymptotic normality properties are studied and a method for the selection of the smoothing parameter by means of the modification of the least-squares cross-validation procedure is proposed.