Discriminant Analysis Programme: jvec=ranpn1(n,p1) - File Exchange

Code covered by the BSD License

Highlights from
Discriminant Analysis Programme

DAP(varargin)
DSEst(data, maxrep, DSdim) Donoho-Stahel robust dispersion/location estimation method for gaussian data
DSWeightings(directions, DSPa... Computes maximum wheightings by data projection through unit norm vectors.
DataImport(samples, valid, da...
Delta=computeDeltaMatrix(TLis...
ExitSession(hObject) Exit menu
FList=compute_F_matrices(B, m...
ImportDonohoStahelDimensions Loads the the Donoho-Stahel Estimator's dimensional constants data file
InputInfo(samples, preDefInpu...
Q=galg(TList, numGrp) G algorithm
SEst(data, maxrep, bdp) Computes biweight multivariate S-estimator for location/dispersion with algorithm of
T=computeTMatrix(TList, numGr...
TList=compute_T_matrices(FLis...
Tbsb(c,p);
Tbsc(alpha,p); constant for Tukey Biweight S
classifyRuleCoef(m_model, m_d... Computes the Classification Rule Coefficients
computeCPCModel(covList, m_co...
computeCPCSigmaList(B, LList,...
computeEntries_F_matrices(FLi...
computeEntries_F_matrices(m, ...
computeInvCovList(covList, nu...
computeLikelihoodRatioTest(mo... testStatistic = testStatistic + 2 * (m_constants.numGrp - 1) * m_constants.numVar; % AIC for Flury Decomposition of Chi Square
computeLinearModel(covList, m... Linear Model Algorithm
computeProportionalModel(covL... Proportional Covariance Matrices Algorithm
crossValidation(model, m_dap) Cross-Validation
discrimRuleCoef(m_model, m_da... Computes the Discrimination Rule Coefficients, that is, the Discriminant
dispList(list,outputStr)
displayCPCModel(cpcCovList, L...
displayCellList(model, cellLi...
displayCoefCellList(model, ce...
displayCoefList(coefList)
displayLikelihoodRatioTest(pV...
displayLinearModel(pooledCov,...
displayProportionalModel(prop...
displayQuadraticModel(quadrat...
falg(covList, numVar, numGrp) F algorithm
huber(weightings, locationCon... Huber's function
jvec=ranpn1(n,p1) Returns the subsamples' indexes
ksiint(c,s,p);
linearCVCoefficent(D, dataEle... Linear Cross Validation Coefficent
linearRule(location, D, dataE... Linear Discriminant Rule
linearSampleClassification(di...
mahalanobis(dat,meanvct,covma... Computes the mahalanobis distances.
plotClassification(m_model, c... Plots the classified data along with discrimination regions
plotClassificationBoundaries(... Plots the modeled concentration bounderies for the groups
plotDiscriminationRegions(m_m... Plots the discrimination regions for the groups
plotMalclassification(m_model... Plots the malclassified data along with discrimination regions
plotNormalProbability(m_dap)
psibiweight(x,c) Computes Tukey's biweight psi function with constant c for all
quadraticCVCoefficent(D, data... Quadratic Cross Validation Coefficent
quadraticRule(location, D, da... Quadratic Discriminant Rule
quadraticSampleClassification...
randomset(tot,nel,seed)
randomset1(tot,nel)
rhobiweight(x,c) Computes Tukey's biweight rho function with constant c for all
sestck(x,start,c,k,tol) Computes Tukey's biweight objectief function (scale) corresponding
unitVectors(vecDim, numVector... Computes unit norm vectors either from a gaussian distribution for
validateData(datasets, sample...
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from Discriminant Analysis Programme by Bartolomeu Rabacal
Discrimination and Classification of data to and from groups with classical/robust estimation

jvec=ranpn1(n,p1)
function jvec=ranpn1(n,p1) % Returns the subsamples' indexes xran=rand(n,1); [au,vec]=sort(xran); jvec=vec(1:p1);

Highlights from Discriminant Analysis Programme

Highlights from
Discriminant Analysis Programme