上海卡贝信息技术有限公司
   

介绍

ANUSPLIN是一款十分流行的气象变量插值软件,还包括数据诊断及统计分析等等功能。当前最新版本:ANUSPLIN Vrsn 4.4。

The ANUSPLIN package provides a facility for transparent analysis and interpolation of noisy multi-variate data using thin plate smoothing splines, through comprehensive statistical analyses, data diagnostics and spatially distributed standard errors. It also supports flexible data input and surface interrogation procedures.

The original thin plate (formerly Laplacian) smoothing spline surface fitting technique was described by Wahba (1979), with modifications for larger data sets due to Bates and Wahba (1982), Elden (1984), Hutchinson (1984) and Hutchinson and de Hoog (1985). The extension to partial splines is based on Bateset al. (1987). This allows for the incorporation of parametric linear sub-models (or covariates), in addition to the independent spline variables. This is a robust way of allowing for additional dependencies, provided a parametric form for these dependencies can be determined. In the limiting case of no independent spline variables (not currently permitted), the procedure would become simple multi-variate linear regression.

Thin plate smoothing splines can in fact be viewed as a generalisation of standard multi-variate linear regression, in which the parametric model is replaced by a suitably smooth non-parametric function. The degree of smoothness, or inversely the degree of complexity, of the fitted function is usually determined automatically from the data by minimising a measure of predictive error of the fitted surface given by the generalised cross validation (GCV). Theoretical justification of the GCV and demonstration of its performance on simulated data have been given by Craven and Wahba (1979).

A comprehensive introduction to the technique of thin plate smoothing splines, with various extensions, is given in Wahba (1990). A brief overview of the basic theory and applications to spatial interpolation of monthly mean climate is given in Hutchinson (1991a). More comprehensive discussion of the algorithms and associated statistical analyses, and comparisons with kriging, are given in Hutchinson (1993) and Hutchinson Gessler (1994). Recent applications to annual and daily precipitation data have been described by Hutchinson (1995, 1998ab).

It is often convenient, particularly when processing climate data, to process several surfaces simultaneously. ANUSPLIN now allows for arbitrarily many such surfaces and introduces the concept of "surface independent variables", so that independent variables may change systematically from surface to surface. ANUSPLIN permits systematic interrogation of these surfaces, and their standard errors, in both point and grid form. ANUSPLIN also permits transformations of both independent and dependent variables.

功能特征

  • SPLINA and SPLINB have been combined into a single program now called SPLINE
  • SPLINE can specify the number of knots, removing the need for a separate run of SELNOT
  • SPLINE provides a new output diagnostic file with the individual cross validated values of the fitted spline
  • Data files with missing values supported
  • Smoothing can be determined by minimising generalised cross-validation (GCV) or generalised maximum likelihood (GML)
  • AVGCVA and AVGCVB rolled into a single program now called GCVGML

Future development

  • Additional on-line transformations of dependent variables
  • Capacity to fit additive spline models
  • Calculation of partial derivatives of fitted spline functions

请访问官网联系购买事宜

http://fennerschool.anu.edu.au/research/products/anusplin-vrsn-44

 

 

 

 

 

 

 

 

 

 

站点地图|隐私政策|加入我们
Copyright © 2021  上海卡贝信息技术有限公司   All rights reserved.