Regression Options - Maple Help

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Regression Options

 This help page describes the options that may be provided to the regression commands in the Statistics package.  See the Statistics/Regression help page for an overview of the regression commands.

Options for General Fitting

 output = name or string
 When the output = solutionmodule option is provided, a module with two exports, Settings and Results, is returned.  Each export is a procedure that queries the values of the problem settings or solution. The output option can also take as a value one of the following names (or a list of these names): AtkinsonTstatistic, confidenceintervals, CookDstatistic, degreesoffreedom, externallystandardizedresiduals, internallystandardizedresiduals, leastsquaresfunction, leverages, parametervalues, parametervector, residuals, residualmeansquare, residualstandarddeviation, residualsumofsquares, standarderrors, variancecovariancematrix. Any of these names may also be provided as a string.
 Some of these results are not available for all regression commands. Full details about how to use the solution module and descriptions of the setting and result values are provided in the Statistics/Regression/Solution help page.
 weights = Vector
 Provide weights for the data points.  If there are k data points, then a Vector of dimension k may be provided through the weights option.  The ith data point is then weighted by the ith value of the weights Vector. By default, all data points are weighted equally, except for particular models as specified in the help pages for the commands associated with them.  All weights must be positive values.

Options for Linear Fitting

 confidencelevel = realcons
 Specify the confidence level used in computing confidence intervals for the parameters.
 svdtolerance = realcons(nonnegative)
 Set the tolerance that determines whether a singular-value decomposition (SVD) is performed.  This option is available only for the linear regression commands. Normally, a method using QR decomposition is applied.  If it is determined that the system does not have full rank, then an SVD is performed.  The smaller the svdtolerance value, the stricter the criteria for performing an SVD. A value of 0.0 means that an SVD is never performed.  The default value for the svdtolerance option is 1.0e-12.

Options for Nonlinear Fitting

 initialvalues = set(equation), list(equation), list(realcons), or 'Vector'(realcons)
 Provide an initial point. Usually, the initial point is specified as a set or list of equalities $\mathrm{varname}=\mathrm{value}$ when the most common form of input, algebraic form, is used. When  operator form or Matrix form is used, the initial point is specified as a list or Vector of values.
 Because the solvers in the Optimization package only compute local solutions, it is strongly recommended that you provide an appropriate initial point through this option.  All solvers use initial-point information, except the quadratic interpolation method of Optimization[NLPSolve]. The initial point is ignored in this case. For more information, see the Optimization/Methods help page.
 This option only has an effect on nonlinear fitting, but it is accepted by Statistics[Fit] even in the case where linear fitting is used.