Exploring the Latest Pantheon SNIa Dataset by Using Three Kinds of
  Statistics Techniques
  In this work, we explore the cosmological consequences of the latest Type Ia
supernova (SN Ia) data-set, Pantheon, by adopting the $wCDM$ model. The
Pantheon data-set is the largest SN Ia samples till now, which contains 1048
supernovae on the redshift range $0 < z < 2.3$. Here we take into account three
kinds of SN Ia statistics techniques, including: 1. magnitude statistics (MS),
which is the traditional SN Ia statistics technique; 2. flux statistics (FS),
which bases on the flux-averaging (FA) method; 3. improved flux statistics
(IFS), which combines the advantages of MS and FS. It should be mentioned that,
The IFS technique need to scan the $(z_{cut},\Delta z)$ parameters plane, where
$z_{cut}$ and $\Delta z$ are redshift cut-off and redshift interval of FA,
respectively. The results are shown as follows. (1) Using SN data-set only, the
best FA recipe for IFS is $(z_{cut},\Delta z)=(0.1,0.08)$; (2) Comparing to the
old SN data-set, JLA, adopting Pantheon data-set can reduce the $2\sigma$ error
bars of equation of state $w$ by 38\%, 47\% and 53\% for MS, FS and IFS,
respectively; (3) FS gives closer results to other observations, such as Baryon
acoustic oscillations and Cosmic microwave background; (4) Compared with FS and
IFS, MS more favors a Universe that will end in a "big rip".
