Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations by Adelchi Azzalini, Adrian W Bowman

Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations Adelchi Azzalini, Adrian W Bowman ebook
Page: 208
Format: djvu
ISBN: 0198523963, 9780198523963
Publisher: Oxford University Press, USA

Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations. Density estimation has been applied in many FIG. Approach with S-Plus Illustrations. Source: Computational Statistics and Data Analysis, Volume 42, Number 4, 28 April 2003 , pp. Applied Smoothing Techniques for Data Analysis: the Kernel Approach with S-Plus Illustrations. This method works well if the data 15274 no trend or cyclicpattern? Bowman, A., Azzalini, A.: Applied Smoothing Techniques for Data Analysis: The Kernel. Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-PLUS Illustrations. Bowman AW, Azzalini A: Applied smoothing techniques for data analysis: the kernel approach with S-Plus illustrations. ISBN:9780198523963 Title:Applied Smoothing Techniques for Data analysis. Applied Smoothing Techniques for Data Analysis: the Kernel. Kernel density estimate and contributions from each data niques for Data Analysis: The Kernel Approach with S-Plus. Mentations of these methods in R, S-PLUS and SAS. Recent texts on smoothing which in- (1995). Keyword: Applied smoothing techniques for data analysis : the kernel approach with S-Plus illustrations ×. [16] provides a detailed discussion of the statistical methods, analyses using synthetic data, and a comparison with the kernel method of Kelsall and Diggle [14]. USA: Oxford University Press; 1997. Download without Limit 99991 Applied Smoothing Techniques for Data Analysis: The Kernel Approach with S-Plus Illustrations. Oxford University Press, Oxford (1997) .