%0 Journal Article
%A Shipley, B.
%A Hunt, R.
%T Regression smoothers for estimating parameters of growth analyses
%B Annals of Botany
%D 1996
%V 78
%P 569-576
%N 5
%Z 03057364 (ISSN) Cited By (since 1996): 10 Export Date: 26 April 2007
Source: Scopus CODEN: ANBOA doi: 10.1006/anbo.1996.0162 Language
of Original Document: English Correspondence Address: Shipley, B.;
Departement de Biologie; Universite de Sherbrooke Sherbrooke, Que.
J1K 2R1, Canada References: Chambers, J.M., Hastie, T.J., (1992)
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%X The objective of regression smoothers is to obtain predicted values
of a dependent variable and its first derivative from empirical
data without having to assume any particular functional relationship
between the dependent and independent variables. An early variant
of this type of analysis, specifically natural B-splines, was first
applied to growth analyses by Parsons and Hunt in 1981 (Annals of
Botany 48:341-352, 1981). The object of this paper is to describe
and evaluate two recent advances in this area (cubic spline smoothers
and loess smoothers) in the context of plant growth analysis and
compare them to natural B-splines. The accuracies of these methods
are evaluated using simulated data of a type that normally causes
difficulties with other methods. A bootstrap procedure is described
that improves the estimate of the optimal smoother parameter. It
is shown that these smoothers can capture even subtle changes in
relative growth rate. The method is then applied to growth data
of Holcus lanatus.
%K B-splines cubic spline smoothers growth analyses Holcus lanatus loess
relative growth rate RGR growth analysis parameter estimation regression
smoother relative growth rate statistical technique Holcus lanatus
Poaceae
%# brugerolles
%F ShipleyHunt1996
%3 BibTeX type = ARTICLE