Weighted comparison of means

Statistics notes. Weighted comparison of means.

Bilateral Weighted Fuzzy C-Means Clustering

Nowadays, the Fuzzy C-Means method has become one of the most popular clustering methods based on minimization of a criterion function. However, the performance of this clustering algorithm may be significantly degraded in the presence of noise. This paper presents a robust clustering algorithm called Bilateral Weighted Fuzzy CMeans (BWFCM). We used a new objective function that uses some k...

Confidence Interval Estimation of the Mean of Stationary Stochastic Processes: a Comparison of Batch Means and Weighted Batch Means Approach (TECHNICAL NOTE)

Suppose that we have one run of n observations of a stochastic process by means of computer simulation and would like to construct a condifence interval for the steady-state mean of the process. Seeking for independent observations, so that the classical statistical methods could be applied, we can divide the n observations into k batches of length m (n= k.m) or alternatively, transform the cor...

Weighted Power Means of Operators

Let σ1,σ2, · · · ,σn be positive real numbers satisfying n ∑ i=1 σi = 1 and A1,A2, · · · ,An be positive operators. Let Mσ,γ(A) = ( n ∑ i=1 σiA γ i ) 1/γ, γ > 0. It has been shown that lim γ→0+ Mσ,γ exists. Some known inequalities have also been generalized.

On Weighted Randomly Trimmed Means

A class of robust location estimators called weighted randomly trimmed means are introduced and not only their consistency and asymptotic normality are proved, but their influence functions, asymptotic variances and breakdown points are also derived. They possess the same breakdown points as the median, and some of them own higher asymptotic relative efficiencies at the heavy-tailed distributio...