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We investigate the Gaussianity of the 4-year COBE-DMR data (in HEALPix pixelisation) using an analysis based on spherical Haar wavelets. We use all the pixels lying outside the Galactic cut and compute the skewness, kurtosis and scale-scale correlation spectra for the wavelet coefficients at each scale. We also take into account the sensitivity of the method to the orientation of the input signal. We find a detection of non-Gaussianity at $> 99$ per cent level in just one of our statistics. Taking into account the total number of statistics computed, we estimate that the probability of obtaining such a detection by chance for an underlying Gaussian field is 0.69. Therefore, we conclude that the spherical wavelet technique shows no strong evidence of non-Gaussianity in the COBE-DMR data.
We present an analysis of the Gaussianity of the 4-year COBE-DMR data (in HEALPix pixelisation) based on spherical wavelets. The skewness, kurtosis and scale-scale correlation spectra are computed from the detail wavelet coefficients at each scale. T
We derive an optimal linear filter to suppress the noise from the COBE DMR sky maps for a given power spectrum. We then apply the filter to the first-year DMR data, after removing pixels within $20^circ$ of the Galactic plane from the data. The filte
More than a dozen papers analyzing the COBE data have now appeared. We review the different techniques and compare them to a ``brute force likelihood analysis where we invert the full 4038 x 4038 Galaxy-cut pixel covariance matrix. This method is opt
We present an application of the fast Independent Component Analysis method to the COBE-DMR 4yr data. Although the signal-to-noise ratio in the COBE-DMR data is typically $sim 1$, the approach is able to extract the CMB signal with high confidence wh
The first two years of COBE DMR observations of the CMB anisotropy are analyzed and compared with our previously published first year results. The results are consistent, but the addition of the second year of data increases the precision and accurac