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Abstract
We study the statistical characteristics of a box-fitting algorithm to analyze stellar
photometric time series in the search for periodic transits by extrasolar planets.
The algorithm searches for signals characterized by a periodic alternation between
two discrete levels, with much less time spent at the lower level. We present numerical
as well as analytical results to predict the possible detection significance at various
signal parameters. It is shown that the crucial parameter is the effective signal-to-noise
ratio -- the expected depth of the transit divided by the standard deviation of the
measured photometric average within the transit. When this parameter exceeds the value
of 6 we can expect a significant detection of the transit. We show that the box-fitting
algorithm performs better than other methods available in the astronomical literature,
especially for low signal-to-noise ratios.