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Math and StatisticsStatistics and Probability

Nonparametric Tests for Multiple Regression Under Progressive Censoring.

Authors: Hiranmay Majumdar; Pranab Kumar Sen; NORTH CAROLINA UNIV AT CHAPEL HILL DEPT OF BIOSTATISTICS
Abstract:
For continuous observations from time-sequential studies, suitable Cramer-von Mises and Kolmogorov-Smirnov type (nonparametric) statistics (based on linear rank statistics) for testing hypotheses on some multiple regression models are proposed and studied. Asymptotic theory of these tests is provided for both the null and (local) alternative hypotheses situations and is based on the weak convergence of suitable rank order processes (on the D(0,1) space) to certain functions of Brownian Motions. Bahadur efficiency results are also presented. Empirical values of the percentile points of the null distributions of the proposed test statistics, obtained through simulation studies, are also provided. (Author)

Description: Interim rept.
Pages: 35
Report Date: 1976
Contract Number: AFAFOSR273674, PHSNHLI712243
Report Number: A893630

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Keywords relating to this report:
*HYPOTHESES
*NONPARAMETRIC STATISTICS
*REGRESSION ANALYSIS
*SEQUENCES(MATHEMATICS)
*SEQUENCES_MATHEMATICS_
CONVERGENCE
LIFE CYCLE TESTING
MATHEMATICAL MODELS
RANK ORDER STATISTICS
STATISTICAL DISTRIBUTIONS
STATISTICAL TESTS
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