Package: MNM 1.0-4

Klaus Nordhausen

MNM: Multivariate Nonparametric Methods. An Approach Based on Spatial Signs and Ranks

Multivariate tests, estimates and methods based on the identity score, spatial sign score and spatial rank score are provided. The methods include one and c-sample problems, shape estimation and testing, linear regression and principal components. The methodology is described in Oja (2010) <doi:10.1007/978-1-4419-0468-3> and Nordhausen and Oja (2011) <doi:10.18637/jss.v043.i05>.

Authors:Klaus Nordhausen [aut, cre], Jyrki Mottonen [aut], Hannu Oja [aut]

MNM_1.0-4.tar.gz
MNM_1.0-4.tar.gz(r-4.5-noble)MNM_1.0-4.tar.gz(r-4.4-noble)
MNM_1.0-4.tgz(r-4.4-emscripten)MNM_1.0-4.tgz(r-4.3-emscripten)
MNM.pdf |MNM.html✨
MNM/json (API)

# Install 'MNM' in R:
install.packages('MNM', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • beans - Randomized Block Experiment of Plots of Beans

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

2.88 score 1 packages 25 scripts 231 downloads 10 mentions 18 exports 15 dependencies

Last updated 1 years agofrom:d718d21026. Checks:OK: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKDec 25 2024
R-4.5-linuxOKDec 25 2024

Exports:affine.transmv.1sample.estmv.1sample.testmv.2sample.estmv.2way.estmv.2way.testmv.Csample.testmv.ind.testmv.l1lmmv.shape.estmv.shape.testmvPCApairs2plotMvlocplotShapermvpowerexprunifspherespatial.sign2

Dependencies:DBIellipseICSICSNPlatticeMatrixminqamitoolsmvtnormnumDerivRcppRcppArmadilloSpatialNPsurveysurvival

Readme and manuals

Help Manual

Help pageTopics
Multivariate Nonparametric Methods. An Approach Based on Spatial Signs and RanksMNM-package MNM
Function For Affine Data Transformationaffine.trans
Comparisons between Multivariate Linear Modelsanova.mvl1lm
Randomized Block Experiment of Plots of Beansbeans
Coefficients of an mvl1lm Objectcoef.mvl1lm
Fitted Values of an mvl1lm Objectfitted.mvl1lm
Multivariate One Sample Location Estimatesmv.1sample.est
Multivariate Location Testsmv.1sample.test
Multivariate Two Sample Shift Estimatesmv.2sample.est
Treatment Effect Estimates in the Randomized Complete Block Casemv.2way.est
Randomized Complete Block Design.mv.2way.test
C Sample Test of Locationmv.Csample.test
Independence Testmv.ind.test
Linear Regression Based on Identity, Spatial Sign or Spatial Rank Scoresmv.l1lm
Shape Matricesmv.shape.est
Test for Sphericitymv.shape.test
Principal Component AnalysismvPCA
Plotting two numeric matricespairs2
Residual Plot for an mvl1lm Objectplot.mvl1lm
Plotting Method for mvloc Objectsplot.mvloc
Function to Plot Multivariate Location Estimates and Their Confidence Ellipsoids.plotMvloc
Pairwise Scatterplot Matrix of Shape MatricesplotShape
Predicted Values Based on a Model Fitted by mv.l1lmpredict.mvl1lm
Prediction Method for a Principal Component Object of Type mvPCApredict.mvPCA
Printing an Object of Class anovamvl1lmprint.anovamvl1lm
Printing an 'mvcloc' Objectprint.mvcloc
Printing an mvl1lm Objectprint.mvl1lm
Printing an 'mvloc' Objectprint.mvloc
Printing Method for a Principal Component Object of Type mvPCAprint.mvPCA
Residuals of an mvl1lm Objectresiduals.mvl1lm
Random Samples From a Power Exponential Distributionsrmvpowerexp
Random Samples From the Unit Sphererunifsphere
Plotting Method for a Principal Component Object of Type mvPCAplot.mvPCA screeplot.mvPCA
Spatial Signsspatial.sign2
Summarizing an 'mvcloc' Objectsummary.mvcloc
Summary for an mvl1lm Objectsummary.mvl1lm
Summarizing an 'mvloc' Objectsummary.mvloc
Summary for an object of class mvPCA.print.summary.mvPCA summary.mvPCA
Variance-Covariance Matrix of an mvl1lm Objectvcov.mvl1lm