2.4.7 fitMR
Brief Information
Multiple linear regression
Additional Information
Minimum Origin Version Required for all features: Origin 9.0
X-Function not designed for Auto GetN Dialog.
Command Line Usage
1. fitmr dep:=col(D) indep:=col(A):col(C) mrtree:=tr odep:=col(E);
X-Function Execution Options
Please refer to the page for additional option switches when accessing the x-function from script
Variables
Display Name
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Variable Name
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I/O and Type
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Default Value
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Description
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Dependent Data
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dep
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Input
vector
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<unassigned>
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Specify dependent variable data range.
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Independent Data
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indep
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Input
Range
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<unassigned>
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Specify independent variables data range, multiple independent data ranges can be specified. For contiguous ranges, use ':' notation like (1:3) for columns 1 to 3. For non-contiguous ranges, use ',' separated list like (1,3,5).
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Fix Intercept
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fixint
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Input
int
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0
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Set to 1 to fix the intercept in multiple linear regression.
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Fix Intercept At
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intercept
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Input
double
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0
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Specify the value of fixed intercept. This is ignored if fixint is set to 0.
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MR Tree
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mrtree
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Output
TreeNode
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mrt
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Tree variable for holding the result of multiple linear regression.
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Fitted Values
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odep
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Output
vector
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<optional>
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Specify the range to output the fitted values of dependent variable.
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Description
This X-Function performs multiple linear regression for LabTalk usage.
After executing, the tree variables include
v# = The fit variable values, enumerated as in mrt.v1, mrt.v2, mrt.v3, etc.
e# = The Standard Error values, enumerated
p# = The Prob > |t| values, enumerated
t# = The t-value values, enumerated
numX = The number of Independent variables
npts = The number of points fit
dof = The Degress of Freedom
ReducedChiSqr = Reduced Chi Square
SSE = Sum of Squares due to Error
Rvalue = R Value
cod = R-Square (COD)
adrsq = Adjusted R-Square
rmse = Root-MSE (SD)
NormRes = Norm of Residuals
pvalue = Prob>F
fvalue = F Value
MSE = Mean Square Error
MSR = Model Mean Square
SSR = Model Sum of Squares
SST = Sum of Squares Total
Examples
/*
How to perform multiple linear regression on data with three independents
and on dependent in the active sheet and dump the results
*/
// first import some data
filename$ = system.path.program$ + "Samples\Curve Fitting\Multiple Linear Regression.dat";
newbook;
impASC filename$;
// fitting
fitmr dep:=col(D) indep:=col(A):col(C) mrtree:=tr odep:=col(E);
// add some results to a new sheet
newsheet name:=MRResult;
wks.ncols = 5;
// arrange the results to the sheet
col(1)[1]$ = Beta0;
col(1)[2]$ = Beta1;
col(1)[3]$ = Beta2;
col(1)[4]$ = Beta3;
col(2)[L]$ = Value;
col(2)[1] = tr.v1;
col(2)[2] = tr.v2;
col(2)[3] = tr.v3;
col(2)[4] = tr.v4;
col(3)[L]$ = "Standard Error";
col(3)[1] = tr.e1;
col(3)[2] = tr.e2;
col(3)[3] = tr.e3;
col(3)[4] = tr.e4;
col(4)[L]$ = t-Value;
col(4)[1] = tr.t1;
col(4)[2] = tr.t2;
col(4)[3] = tr.t3;
col(4)[4] = tr.t4;
col(5)[L]$ = Prob>|t|;
col(5)[1] = tr.p1;
col(5)[2] = tr.p2;
col(5)[3] = tr.p3;
col(5)[4] = tr.p4;
// dump the result tree
tr.=;
Algorithm
Please refer to our User Guide: Multiple Regression Results.
Keywords:curve fitting
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