A step-by-step guide to non-linear regression analysis of experimental data using a Microsoft Excel spreadsheet

被引:383
作者
Brown, AM [1 ]
机构
[1] Univ Washington, Sch Med, Dept Neurol, Seattle, WA 98195 USA
关键词
Microsoft Excel; non-linear regression; least squares; iteration; goodness of fit; curve fit;
D O I
10.1016/S0169-2607(00)00124-3
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
The objective of this present study was to introduce a simple, easily understood method for carrying out non-linear regression analysis based on user input functions. While it is relatively straightforward to fit data with simple functions such as linear or logarithmic functions, fitting data with more complicated non-linear functions is more difficult. Commercial specialist programmes are available that will carry out this analysis, but these programmes are expensive and are not intuitive to learn. An alternative method described here is to use the SOLVER function of the ubiquitous spreadsheet programme Microsoft Excel, which employs an iterative least squares fitting routine to produce the optimal goodness of fit between data and function. The intent of this paper is to lead the reader through an easily understood step-by-step guide to implementing this method, which can be applied to any function in the form y = f(x), and is well suited to fast, reliable analysis of data in all fields of biology. (C) 2001 Elsevier Science Ireland Ltd. All rights reserved.
引用
收藏
页码:191 / 200
页数:10
相关论文
共 6 条
[1]   Nonlinear regression using spreadsheets [J].
Bowen, WP ;
Jerman, JC .
TRENDS IN PHARMACOLOGICAL SCIENCES, 1995, 16 (12) :413-417
[2]  
Dempster J., 1993, COMPUTER ANAL ELECTR
[3]   WHY, WHEN, AND HOW BIOCHEMISTS SHOULD USE LEAST-SQUARES [J].
JOHNSON, ML .
ANALYTICAL BIOCHEMISTRY, 1992, 206 (02) :215-225
[4]  
Lasdon L. S., 1978, ACM Transactions on Mathematical Software, V4, P34, DOI 10.1145/355769.355773
[5]   FITTING CURVES TO DATA USING NONLINEAR-REGRESSION - A PRACTICAL AND NONMATHEMATICAL REVIEW [J].
MOTULSKY, HJ ;
RANSNAS, LA .
FASEB JOURNAL, 1987, 1 (05) :365-374
[6]  
Smith S., 1992, ORSA J COMPUTING, V4, P2, DOI [10.1287/ijoc.4.1.2, DOI 10.1287/IJ0C.4.1.2]