Refits a standard curve with common nonlinear parameters across groups to provide s.e.’s for linear parameters (R.W. Payne).
Options
PRINT = string tokens |
Printed output from the analysis (model , deviance , summary , estimates , correlations , fittedvalues , accumulated , monitoring ); default mode , summ , esti |
MAXCYCLE = variate |
Maximum number of iterations; default 30 |
METHOD = string token |
Algorithm for fitting nonlinear model (gaussnewton , newtonraphson , fletcherpowell ); default newt |
STEPLENGTHS = scalar or variate |
Initial step lengths for the parameters |
SAVE = regression save structure |
Save structure from this analysis |
INSAVE = regression save structure |
Save structure for the curve fitted by FITCURVE , default takes the most recent regression analysis |
No parameters
Description
RCURVECOMMONNONLINEAR
can be used after a FITCURVE
analysis to refit a standard curve that has common nonlinear parameters across groups. It uses the CALCULATION
option of FIT
, which provides standard errors for the linear parameters. These are unavailable with FITCURVE
.
The INSAVE
option can provide the regression save structure from the FITCURVE
analysis. If this is not set, the save structure from the most recent regression analysis is used. A fault is given if the save structure is not from a FITCURVE
analysis with groups and common nonlinear parameters. The SAVE
option saves the regression save structure from this analysis.
The PRINT
option controls printed output, with the same settings as FITCURVE
. The other options control aspects of the optimization. MAXCYCLE
specifies the maximum number of iterations to be used to estimate the nonlinear parameters; default 30. METHOD
specifies the algorithm to be used. The default is Newton Raphson, which is the same method as FITCURVE
. STEPLENGTHS
defines step lengths for the estimation of the nonlinear parameters. FITCURVE
uses a different strategy from FIT
. It includes nonlinear parameters for all the groups in the model, but constrains them to be equal when they are common across groups. Consequently RCURVECOMMONNONLINEAR
may obtain slightly different parameter estimates from the original FITCURVE
analysis. Modifying these options may enable you to obtain closer results.
Options: PRINT
, MAXCYCLE
, METHOD
, STEPLENGTHS
, SAVE
, INSAVE
.
Parameters: none.
Action with RESTRICT
Any restriction applied to vectors used in the regression model applies also to the results from RCURVECOMMONNONLINEAR
.
See also
Directives: FIT
, FITCURVE
.
Commands for: Regression analysis.
Example
CAPTION 'RCURVECOMMONNONLINEAR example',\ !t('Relationship between yield of sugar from sugar beet',\ 'and phosphorus in different years'); STYLE=meta,plain VARIATE [NVALUES=64] Beetwt,%sugar,SoilP,Sugar READ Beetwt,%sugar,SoilP 7.23 18.5 5.4 7.69 18.0 5.4 24.64 20.1 7.8 26.67 19.8 8.0 39.78 19.5 18.0 44.98 19.3 15.6 41.59 19.7 30.4 44.08 19.8 33.8 48.37 19.4 50.4 44.76 19.0 51.0 49.73 18.6 44.0 51.54 18.5 40.2 47.69 19.0 57.2 45.66 19.4 65.0 50.18 18.6 27.0 47.69 18.7 30.0 8.82 13.8 5.6 1.81 13.9 4.8 15.82 14.5 10.2 9.04 14.0 8.6 24.41 15.0 21.6 22.60 14.1 17.2 26.45 15.2 36.4 20.80 15.3 37.2 28.30 14.2 44.4 22.60 14.7 44.4 14.24 13.5 41.0 35.94 15.6 30.2 25.54 15.8 60.8 27.13 15.6 47.0 31.42 15.6 27.0 34.13 15.4 29.0 19.90 16.1 3.0 20.60 16.0 2.0 34.70 16.7 6.2 35.40 16.4 6.2 46.80 17.1 19.8 40.50 16.9 17.2 43.00 16.9 29.6 48.60 17.1 28.0 47.30 17.0 42.8 41.30 17.1 46.2 44.30 17.0 36.6 47.60 16.6 40.0 45.60 17.0 42.2 44.60 17.0 52.0 44.00 17.2 23.4 40.10 16.6 28.0 14.35 16.1 4.0 14.35 15.5 3.8 26.71 16.6 8.0 25.12 16.4 6.4 33.39 17.2 18.2 33.79 16.2 14.8 36.68 17.0 35.0 33.69 16.8 29.6 34.98 17.0 37.2 35.78 17.0 40.0 42.06 17.2 39.6 38.77 17.3 36.8 40.66 17.3 52.4 37.28 17.2 45.6 34.68 17.3 22.0 32.59 17.2 26.0 : CALCULATE Sugar = Beetwt * %sugar / 100 FACTOR [LEVELS=4; VALUES=16(1...4)] Year MODEL Sugar TERMS SoilP*Year FITCURVE [PRINT=model,estimates; CURVE=lexp] SoilP ADD Year & SoilP.Year & [PRINT=accumulated; NONLINEAR=separate; FPROBABILITY=yes] DROP [PRINT=*; NONLINEAR=common] RCURVECOMMONNONLINEAR