ROBUST INFERENCE FOR LOCATION PARAMETERS

Estimating measures of location is a fundamental
statistical problem. The sample mean is not always a
good choice to estimate location because it is
not resistant to the influence of outliers. To treat
this problem in a precise manner when nonnormality is
present, we may use robust location estimates. In
this work, we present a number of robust location
functionals and deter- mine their breakdown point and
influence function. We study robust location
estimates such as the sample trimmed mean, the sample
Winsorized mean and estimates based on symmetric
quantiles. Confidence interval estimation and
hypothesis testing are examined from a robust
perspective. Both the one-sample case and the
two-sample case are considered, the latter under two
situations : independence and dependence. A few
practical examples illustrate the study. Some R
programmes are presented in this book.

Autorentext

BEI FENG graduated in mathematics (Wuhan Normal Institute,Hankou Branch, China, 1985),and obtained a Master Science in Statistics (Laval University, Canada, 2003). She works for Research unit on children's psychosocial maladjustment, Laval University, Canada. As a statistician, she has many research interests especially in robust statistics.

Klappentext

Estimating measures of location is a fundamentalstatistical problem. The sample mean is not always a good choice to estimate location because it isnot resistant to the influence of outliers. To treatthis problem in a precise manner when nonnormality ispresent, we may use robust location estimates. Inthis work, we present a number of robust locationfunctionals and deter- mine their breakdown point andinfluence function. We study robust locationestimates such as the sample trimmed mean, the sampleWinsorized mean and estimates based on symmetricquantiles. Confidence interval estimation andhypothesis testing are examined from a robustperspective. Both the one-sample case and thetwo-sample case are considered, the latter under twosituations : independence and dependence. A fewpractical examples illustrate the study. Some Rprogrammes are presented in this book.