  It is possible that the astrophysical {samples} are polluted by some
outliers, which might belong to a different sub-class. By removing the
outliers, the underline statistical feature may be revealed. {A more reliable
correlation can be used as a standard candle relation for the cosmological
study.} We present outlier searching for gamma-ray bursts with Partitioning
Around Medoids (PAM) method. In this work, we choose three parameters from the
sample, while all of them having rest-frame spectral time lag ($\tau_{\rm
lag,i}$). In most cases, the outliers are GRBs 980425B and 030528A. Linear
regression is carried out for the sample without the outliers. Some of them
have passed hypothesis testing, while others have not. However, even for the
passed sample, the correlation is not very significant. More parameter
combinations should be considered in the future work.
