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O

ObliminCriteria - Class in com.itemanalysis.psychometrics.factoranalysis
 
ObliminCriteria() - Constructor for class com.itemanalysis.psychometrics.factoranalysis.ObliminCriteria
 
ObliminCriteria(double) - Constructor for class com.itemanalysis.psychometrics.factoranalysis.ObliminCriteria
 
observedStandardDeviation() - Method in class com.itemanalysis.psychometrics.irt.estimation.RaschScaleQualityStatistics
Observed standard deviation of the estimate.
observedVariance() - Method in class com.itemanalysis.psychometrics.irt.estimation.RaschScaleQualityStatistics
Observed variance of the estimate.
oneTailedFishersExact(int, int, int, int) - Static method in class com.itemanalysis.psychometrics.optimization.SloppyMath
Find a one-tailed Fisher's exact probability.
optchk_f77(int, double[], double[], double[], double[], double[], int[], int[], double, double[], int[], int[], int[], int[], double[], int[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin
The optchk_f77 method checks the input for reasonableness.
optchk_f77(int, double[], double[], double[], double[], double[], int[], int[], double, double[], int[], int[], int[], int[], double[], int[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77
The optchk_f77 method checks the input for reasonableness.
optdrv_f77(int, double[], Uncmin_methods, double[], double[], int[], int[], int[], int[], int[], int[], int[], double[], double[], double[], double[], double[], double[], double[], int[], double[][], double[], double[], double[], double[], double[], double[], double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin
The optdrv_f77 method is the driver for the nonlinear optimization problem.
optdrv_f77(int, double[], Uncmin_methods, double[], double[], int[], int[], int[], int[], int[], int[], int[], double[], double[], double[], double[], double[], double[], double[], int[], double[][], double[], double[], double[], double[], double[], double[], double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77
The optdrv_f77 method is the driver for the nonlinear optimization problem.
optif0_f77(int, double[], Uncmin_methods, double[], double[], double[], int[], double[][], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin
The optif0_f77 method minimizes a smooth nonlinear function of n variables.
optif0_f77(int, double[], Uncmin_methods, double[], double[], double[], int[], double[][], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77
The optif0_f77 method minimizes a smooth nonlinear function of n variables.
optif9_f77(int, double[], Uncmin_methods, double[], double[], int[], int[], int[], int[], int[], int[], int[], double[], double[], double[], double[], double[], double[], double[], int[], double[][], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin
The optif9_f77 method minimizes a smooth nonlinear function of n variables.
optif9_f77(int, double[], Uncmin_methods, double[], double[], int[], int[], int[], int[], int[], int[], int[], double[], double[], double[], double[], double[], double[], double[], int[], double[][], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77
The optif9_f77 method minimizes a smooth nonlinear function of n variables.
optstp_f77(int, double[], double[], double[], double[], int[], int[], int[], double[], double[], double[], double[], int[], int[], boolean[], int[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin
The optstp_f77 method determines whether the algorithm should terminate due to any of the following: 1) problem solved within user tolerance 2) convergence within user tolerance 3) iteration limit reached 4) divergence or too restrictive maximum step (stepmx) suspected Translated by Steve Verrill, May 12, 1998.
optstp_f77(int, double[], double[], double[], double[], int[], int[], int[], double[], double[], double[], double[], int[], int[], boolean[], int[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77
The optstp_f77 method determines whether the algorithm should terminate due to any of the following: 1) problem solved within user tolerance 2) convergence within user tolerance 3) iteration limit reached 4) divergence or too restrictive maximum step (stepmx) suspected Translated by Steve Verrill, May 12, 1998.
outputToFile - Variable in class com.itemanalysis.psychometrics.optimization.QNMinimizer
 
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