Gray bootstrap method for estimating frequency-varying random vibration signals with small samples

Estimating misclassification error with small samples via bootstrap cross-validation

MOTIVATION Estimation of misclassification error has received increasing attention in clinical diagnosis and bioinformatics studies, especially in small sample studies with microarray data. Current error estimation methods are not satisfactory because they either have large variability (such as leave-one-out cross-validation) or large bias (such as resubstitution and leave-one-out bootstrap). W...

Quasi-Random Methods for Estimating Integrals Using Relatively Small Samples

Much of the recent work dealing with quasi-random methods has been aimed at establishing the best possible asymptotic rates of convergence to zero of the error resulting when a finite-dimensional integral is replaced by a finite sum of integrand values. In contrast with this perspective to concentrate on asymptotic convergence rates, this paper emphasizes quasi-random methods that are effective...

Understanding random Vibration signals

Estimating dimension From small samples

Dclails of a ncw algorirh~n lo cstimatc thc dirnc~~sion of a mcasurc tioru point s a m p l a arc clescribcd, T!ic ncw algorill~rn emphasizes rhal di~ncnsion ncctl no( be Il~e sarnc at dl scnlcs, 1l1a1 is, t l ~c r c ncctl not bc a "scaling rcgion. '~Ilc i\\gorilhm is ucriLcd with Gaussian o~c,~surcs and is found to bc rcliablc ancl hirvc Lcss domanding clnla rctl\~ircmcnts t h a n coavcn~ional ...

Classification Rule for Small Samples: A Bootstrap Approach

#1 Dept. of Statistics, Islamic University, Kushtia, Bangladesh, Phone no. +8801718698811 #2 Dept. of Statistics, Islamic University, Kushtia, Bangladesh, Phone no. +8801716657066 #3 Dept. of Statistics, Jahangirnagar University, Savar, Dhaka, Bangladesh, Phone no. +8801711145041 ABSTRACT In a recent year, classification is computer implemented and most popular data mining technique. Thus in th...