Christopher R. Genovese, Christopher J. Miller, Robert C. Nichol, Mihir Arjunwadkar, and Larry Wasserman
CMB fluctuations provide clues to the Universe's structure and composition shortly after the Big Bang that are critical for testing cosmological models. For example, CMB data can be used to determine what portion of the Universe is composed of ordinary matter versus the mysterious dark matter and dark energy. To this end, cosmologists usually summarize the fluctuations by the power spectrum, which gives the variance as a function of angular frequency. The spectrum's shape, and in particular the location and height of its peaks, relates directly to the parameters in the cosmological models. Thus, a critical statistical question is how accurately can these peaks be estimated.
We use recently developed techniques to construct a nonparametric
confidence set for the unknown CMB spectrum. Our estimated spectrum,
based on minimal assumptions, closely matches the model-based
estimates used by cosmologists, but we can make a wide range of
additional inferences. We apply these techniques to test various
models and to extract confidence intervals on cosmological parameters
of interest. Our analysis shows that, even without parametric
assumptions, the first peak is resolved accurately with current data
but that the second and third peaks are not.
Keywords: Confidence sets, nonparametric regression, cosmology