- D - Variable in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
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- d - Variable in class com.itemanalysis.psychometrics.optimization.QNMinimizer.QNInfo
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- data - Variable in class com.itemanalysis.psychometrics.polycor.AbstractPolychoricCorrelation
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- DataType - Enum in com.itemanalysis.psychometrics.data
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Copyright 2012 J.
- daxpy_f77(int, double, double[], int, double[], int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
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This method multiplies a constant times a vector and adds the product
to another vector --- dy[ ] = da*dx[ ] + dy[ ].
- dcopy_f77(int, double[], int, double[], int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
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This method copies the vector dx[ ] to the vector dy[ ].
- dcopyp_f77(int, double[], double[], int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
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This method copies a portion of vector x[ ] to the corresponding
portion of vector y[ ].
- ddot_f77(int, double[], int, double[], int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
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This method calculates the dot product of two vectors.
- Deciles - Class in com.itemanalysis.psychometrics.statistics
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- Deciles() - Constructor for class com.itemanalysis.psychometrics.statistics.Deciles
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- deepCopy(int[][]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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- DEFAULT_INITIAL_RADIUS - Static variable in class com.itemanalysis.psychometrics.optimization.BOBYQAOptimizer
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- DEFAULT_STOPPING_RADIUS - Static variable in class com.itemanalysis.psychometrics.optimization.BOBYQAOptimizer
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- DefaultEMStatusListener - Class in com.itemanalysis.psychometrics.irt.estimation
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An example EMStatusListener.
- DefaultEMStatusListener() - Constructor for class com.itemanalysis.psychometrics.irt.estimation.DefaultEMStatusListener
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- DefaultItemScoring - Class in com.itemanalysis.psychometrics.measurement
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The default implementation of the ItemScoring interface.
- DefaultItemScoring() - Constructor for class com.itemanalysis.psychometrics.measurement.DefaultItemScoring
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- DefaultItemScoring(boolean) - Constructor for class com.itemanalysis.psychometrics.measurement.DefaultItemScoring
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- DefaultItemScoring.ItemResponseComparator - Class in com.itemanalysis.psychometrics.measurement
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Sort Strings before Doubles.
- DefaultLinearTransformation - Class in com.itemanalysis.psychometrics.scaling
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- DefaultLinearTransformation(Double, Double, Double, Double) - Constructor for class com.itemanalysis.psychometrics.scaling.DefaultLinearTransformation
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- DefaultLinearTransformation(double, double, double, double, LinearTransformationType) - Constructor for class com.itemanalysis.psychometrics.scaling.DefaultLinearTransformation
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Constructor for two different ways of creating the transformation coefficients.
- DefaultLinearTransformation(double, double) - Constructor for class com.itemanalysis.psychometrics.scaling.DefaultLinearTransformation
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- DefaultLinearTransformation() - Constructor for class com.itemanalysis.psychometrics.scaling.DefaultLinearTransformation
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- defaultScoreWeights() - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModel
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- defaultScoreWeights() - Method in class com.itemanalysis.psychometrics.irt.model.AbstractItemResponseModelWithGradient
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- DefaultUncminOptimizer - Class in com.itemanalysis.psychometrics.uncmin
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Provides a more user friendly interface to Uncmin_f77.
- DefaultUncminOptimizer() - Constructor for class com.itemanalysis.psychometrics.uncmin.DefaultUncminOptimizer
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- DefaultUncminOptimizer(int) - Constructor for class com.itemanalysis.psychometrics.uncmin.DefaultUncminOptimizer
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- DefaultUncminOptimizer(boolean) - Constructor for class com.itemanalysis.psychometrics.uncmin.DefaultUncminOptimizer
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- DefaultUncminStatusListener - Class in com.itemanalysis.psychometrics.uncmin
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- DefaultUncminStatusListener() - Constructor for class com.itemanalysis.psychometrics.uncmin.DefaultUncminStatusListener
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- density(double) - Method in class com.itemanalysis.psychometrics.kernel.LeastSquaresCrossValidation
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- density(double, int) - Method in class com.itemanalysis.psychometrics.kernel.LeastSquaresCrossValidation
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- density(RealMatrix) - Method in interface com.itemanalysis.psychometrics.mixture.ComponentDistribution
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- density(RealMatrix) - Method in class com.itemanalysis.psychometrics.mixture.MvNormalComponentDistribution
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- DensityEstimationType - Enum in com.itemanalysis.psychometrics.irt.estimation
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- derivativeAt(double[]) - Method in class com.itemanalysis.psychometrics.analysis.AbstractDiffFunction
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- derivativeAt(double[]) - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemLogLikelihood
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Method required for DiffFunction interface to QNMinimizer
See ItemDichotomous.h in ETIRM
- derivativeAt(double[]) - Method in interface com.itemanalysis.psychometrics.irt.estimation.ItemLogLikelihoodFunction
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Computes gradientAt of item likelihood function at item parameter values.
- derivativeAt(float[]) - Method in interface com.itemanalysis.psychometrics.optimization.DiffFloatFunction
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Returns the first-derivative vector at the input location.
- derivativeAt(double[]) - Method in interface com.itemanalysis.psychometrics.optimization.DiffFunction
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Returns the first-derivative vector at the input location.
- derivLogLikelihood(double) - Method in class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee
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First derivative of loglikelihood with respect to theta.
- derivLogLikelihood(DerivativeStructure) - Method in class com.itemanalysis.psychometrics.irt.estimation.IrtExaminee
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Returns first derivative of loglikelihood using DerivativeStructure per interface requirements
- derivTheta(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
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Derivative from Mathematica.
- derivTheta(double) - Method in class com.itemanalysis.psychometrics.irt.model.Irm4PL
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- derivTheta(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM
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First derivative of item response model with respect to theta.
- derivTheta(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGPCM2
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Partial derivative with respect to theta.
- derivTheta(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmGRM
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Partial derivative wrt Theta.
- derivTheta(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM
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Partial derivative with respect to theta.
- derivTheta(double) - Method in class com.itemanalysis.psychometrics.irt.model.IrmPCM2
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First derivative of item response model with respect to theta.
- derivTheta(double) - Method in interface com.itemanalysis.psychometrics.irt.model.ItemResponseModel
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Computes the first derivative with respect to person ability.
- derivTheta2(double, int) - Method in class com.itemanalysis.psychometrics.irt.model.Irm3PL
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From Equating recipes.
- df - Variable in class com.itemanalysis.psychometrics.polycor.PolychoricMaximumLikelihood
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- dfault_f77(int) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin
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The dfault_f77 method sets default values for each input
variable to the minimization algorithm.
- dfault_f77(int, double[], double[], double[], int[], int[], int[], int[], int[], int[], int[], double[], double[], double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77
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The dfault_f77 method sets default values for each input
variable to the minimization algorithm.
- diag(int[][]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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Returns diagonal elements of the given (square) matrix.
- DiagonalMatrix - Class in com.itemanalysis.psychometrics.measurement
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A diagonal matrix.
- DiagonalMatrix(double[]) - Constructor for class com.itemanalysis.psychometrics.measurement.DiagonalMatrix
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Creates a matrix with diagonal elements set to x.
- DiagonalMatrix(RealMatrix) - Constructor for class com.itemanalysis.psychometrics.measurement.DiagonalMatrix
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Extracts the diagonal elements from a matrix.
- diagonalSum() - Method in class com.itemanalysis.psychometrics.polycor.CovarianceMatrix
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- DiffFloatFunction - Interface in com.itemanalysis.psychometrics.optimization
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An interface for once-differentiable double-valued functions over
double arrays.
- DiffFunction - Interface in com.itemanalysis.psychometrics.optimization
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An interface for once-differentiable double-valued functions over
double arrays.
- DiscriminationType - Enum in com.itemanalysis.psychometrics.measurement
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- DistributionApproximation - Interface in com.itemanalysis.psychometrics.distribution
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An interface for distribution approximations such as those used for quadrature points and weights in
numeric integration.
- distributionName() - Method in interface com.itemanalysis.psychometrics.irt.estimation.ItemParamPrior
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- distributionName() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorBeta
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- distributionName() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorBeta4
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- distributionName() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorLogNormal
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- distributionName() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemParamPriorNormal
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- divideInPlace(double[], double) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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Divides the values in this array by b.
- dnrm2_f77(int, double[], int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
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This method calculates the Euclidean norm of the vector
stored in dx[ ] with storage increment incx.
- dnrm2p_f77(int, double[], int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
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This method calculates the Euclidean norm of a portion
of a vector x[ ].
- dogdrv_f77(int, double[], double[], double[], double[][], double[], double[], double[], Uncmin_methods, double[], double[], double[], double[], int[], boolean[], double[], double[], double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin
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The dogdrv_f77 method finds the next Newton iterate (xpls) by the double dogleg
method.
- dogdrv_f77(int, double[], double[], double[], double[][], double[], double[], double[], Uncmin_methods, double[], double[], double[], double[], int[], boolean[], double[], double[], double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77
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The dogdrv_f77 method finds the next Newton iterate (xpls) by the double dogleg
method.
- dogstp_f77(int, double[], double[][], double[], double[], double, double[], boolean[], boolean[], double[], double[], double[], double[], double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin
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The dogstp_f77 method finds the new step by the double dogleg
appproach.
- dogstp_f77(int, double[], double[][], double[], double[], double, double[], boolean[], boolean[], double[], double[], double[], double[], double[], double[]) - Method in class com.itemanalysis.psychometrics.uncmin.Uncmin_f77
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The dogstp_f77 method finds the new step by the double dogleg
appproach.
- domainDimension() - Method in class com.itemanalysis.psychometrics.irt.estimation.ItemLogLikelihood
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Method required for DiffFunction interface to QNMinimizer
- domainDimension() - Method in interface com.itemanalysis.psychometrics.irt.estimation.ItemLogLikelihoodFunction
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For DiffFunction interface.
- domainDimension() - Method in interface com.itemanalysis.psychometrics.optimization.FloatFunction
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Returns the number of dimensions in the function's domain
- domainDimension() - Method in interface com.itemanalysis.psychometrics.optimization.Function
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Returns the number of dimensions in the function's domain
- doOptimize() - Method in class com.itemanalysis.psychometrics.optimization.BOBYQAOptimizer
- dotProduct(double[], double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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Assumes that both arrays have same length.
- doubleArrayToFloatArray(double[]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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- doubleArrayToFloatArray(double[][]) - Static method in class com.itemanalysis.psychometrics.optimization.ArrayMath
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- doubleIterator() - Method in interface com.itemanalysis.psychometrics.measurement.ItemResponseSummary
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- doubleIterator() - Method in class com.itemanalysis.psychometrics.measurement.NumericItemResponseSummary
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- doubleIterator() - Method in class com.itemanalysis.psychometrics.measurement.TextItemResponseSummary
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- doubleResponseMap - Variable in class com.itemanalysis.psychometrics.measurement.AbstractItemResponseSummary
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- doubleScoreMap - Variable in class com.itemanalysis.psychometrics.measurement.AbstractItemResponseSummary
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- dropStatus() - Method in class com.itemanalysis.psychometrics.irt.model.RaschRatingScaleGroup
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Status of the item with response to dropping.
- drotg_f77(double[]) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
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This method constructs a Givens plane rotation.
- dscal_f77(int, double, double[], int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
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This method scales a vector by a constant.
- dscalp_f77(int, double, double[], int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
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This method scales a portion of a vector by a constant.
- dswap_f77(int, double[], int, double[], int) - Static method in class com.itemanalysis.psychometrics.uncmin.Blas_f77
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This method interchanges two vectors.