Multivariate Nonparametric Methods. An Approach Based on Spatial Signs and Ranks
Function For Affine Data Transformation
Comparisons between Multivariate Linear Models
Coefficients of an mvl1lm Object
Fitted Values of an mvl1lm Object
tools:::Rd_package_title("MNM")
Multivariate One Sample Location Estimates
Multivariate Location Tests
Multivariate Two Sample Shift Estimates
Treatment Effect Estimates in the Randomized Complete Block Case
Randomized Complete Block Design.
C Sample Test of Location
Independence Test
Linear Regression Based on Identity, Spatial Sign or Spatial Rank Scor...
Shape Matrices
Test for Sphericity
Principal Component Analysis
Plotting two numeric matrices
Residual Plot for an mvl1lm Object
Plotting Method for mvloc Objects
Function to Plot Multivariate Location Estimates and Their Confidence ...
Pairwise Scatterplot Matrix of Shape Matrices
Predicted Values Based on a Model Fitted by mv.l1lm
Prediction Method for a Principal Component Object of Type mvPCA
Printing an Object of Class anovamvl1lm
Printing an 'mvcloc' Object
Printing an mvl1lm Object
Printing an 'mvloc' Object
Printing Method for a Principal Component Object of Type mvPCA
Residuals of an mvl1lm Object
Random Samples From a Power Exponential Distributions
Random Samples From the Unit Sphere
Plotting Method for a Principal Component Object of Type mvPCA
Spatial Signs
Summarizing an 'mvcloc' Object
Summary for an mvl1lm Object
Summarizing an 'mvloc' Object
Summary for an object of class mvPCA.
Variance-Covariance Matrix of an mvl1lm Object
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>.