jointnormalTest {QRMlib}R Documentation

Test of Multivariate Normality

Description

provides test of multivariate normality based on analysing Mahalanobis distances

Usage

jointnormalTest(data, dist="chisquare")

Arguments

data matrix of data with each row representing an observation
dist "chisquare" performs test against chi-squared distribution, which is an approximation; "beta" performs test against a scaled beta

Details

see pages 69-70 of QRM

Value

p-value for Kolmogorov-Smirnov test

Side Effects

a QQplot against the reference distribution is created

See Also

MardiaTest

Examples

data(DJ);
Ret.DJ <- mk.returns(DJ);
selection1 <- c("AXP","EK","BA","C","KO","MSFT",
                "HWP","INTC","JPM","DIS");
partialDJ30dailyTS <- Ret.DJ[,selection1];
#Choose only the data from 1/1/1993 to 12/31/2000.  
partialDJ30daily <- window(partialDJ30dailyTS,from="1993-01-01", 
                               to="2000-12-31");
partialDJ30dailyMatrix <- seriesData(partialDJ30daily);
#Note the tests on the ten stocks selected from DJ30 fail the test miserably
#except possibly the quarterly values.  The QQ plots are very revealing. 
#See p. 72 in QRM Book.
jointnormalTest(partialDJ30dailyMatrix);

[Package QRMlib version 1.4.4 Index]