  This work describes Cosmic Microwave Background (CMB) data analysis
algorithms and their implementations, developed to produce a pixelized map of
the sky and a corresponding pixel-pixel noise correlation matrix from time
ordered data for a CMB mapping experiment. We discuss in turn algorithms for
estimating noise properties from the time ordered data, techniques for
manipulating the time ordered data, and a number of variants of the maximum
likelihood map-making procedure. We pay particular attention to issues
pertinent to real CMB data, and present ways of incorporating them within the
framework of maximum likelihood map-making. Making a map of the sky is shown to
be not only an intermediate step rendering an image of the sky, but also an
important diagnostic stage, when tests for and/or removal of systematic effects
can efficiently be performed. The case under study is the MAXIMA data set.
However, the methods discussed are expected to be applicable to the analysis of
other current and forthcoming CMB experiments.
