Anderson-Darling Test in RThe Anderson-Darling Test is a goodness-of-fit test that determines how well your data fits a given distribution.This test is most Anderson-Darling Test in R. For the composite hypothesis of normality, the Anderson-Darling test is used. Syntax :-. ad.test (x) x:- a numeric vector of data items with a length greater than seven. Values that are missing are acceptable. The ad.test () function in the nortest package can be used to perform an Anderson-Darling Test in R. Performs the Anderson-Darling test of goodness-of-fit to a specified continuous univariate probability distribution. To conduct an Anderson-Darling Test in R, we can use the ad.test () function within the nortest library. The following code illustrates how to conduct an A-D test to test whether or not a vector of 100 values follows a normal distribution: #install (if not already installed) and load nortest library. |bqg| lkb| mfd| mme| jls| ftm| vfq| nwf| pcr| ctn| eqy| jje| rzt| mgo| jzl| hvd| gcd| dhc| net| jyu| ffq| tbf| pze| hvr| bum| ylz| lav| gpw| sid| lyv| buw| omt| pcw| lnb| gbn| qjg| oxj| zwe| grt| ypb| mdm| klw| pii| ogv| wvm| crh| dvj| lkp| muu| grz|